Jobs for AI Security Engineers

Research and security engineering role focused on detecting and evaluating misalignment in frontier AI systems. Responsibilities include researching automated methods to find misalignment (research sabotage, reward-seeking, deceptive alignment), building and running alignment evaluations for loss-of-control risks, conducting pre-deployment testing with frontier AI companies, publishing technical research, designing evaluation software and tooling, and threat modeling for model safety. Work directly impacts deployment decisions and safety improvements at frontier AI labs and informs UK government policy.

• AI Red Teaming
• Security Research

Security Operations AI Engineer at 66degrees responsible for AI/ML information security operations and engineering. Develops AI-specific incident response playbooks covering prompt injection, model poisoning, and adversarial attacks. Engineers detection logic and telemetry for identifying AI/ML security events. Monitors and secures generative AI systems, LLMs, and AI-powered applications. Contributes to AI governance frameworks and policies. Analyzes security implications of new AI/ML tools before production deployment. Participates in threat intelligence for emerging AI vulnerabilities. Reviews AI model robustness against adversarial inputs and data privacy protections. Contract position requiring 24/7 availability for critical security incidents.

• Detection & Response
• LLM Security
• MLSecOps

Application Security Consultant performing hands-on assessments of AI/LLM-powered applications and agentic AI systems. Responsibilities include testing for prompt injection, model bypass, excessive agency, tool-calling exploitation, and RAG poisoning attacks mapped to OWASP Top 10 for LLM Applications and Agentic Applications. Builds AI-driven tooling, custom agents, and automation harnesses leveraging LLMs to improve testing coverage and efficiency. Conducts source code reviews, threat modeling, and architecture reviews. Contributes to AI security research and industry publications.

• AI Red Teaming
• Application Security
• LLM Security

Lead application and AI security strategy across Blink Health's infrastructure. Secure LLM integrations, AI agents, and RAG systems through design reviews and threat modeling. Develop secure patterns for prompt handling, model governance, and AI data protection. Establish secure-by-default practices via SAST/DAST automation, architecture guidance, and DevSecOps maturity. Perform threat modeling and penetration testing for critical systems. Mentor security engineers and influence engineering teams through technical leadership. Leverage AI tooling to improve security operations efficiency.

• Application Security
• LLM Security
• MLSecOps

Lead technical strategy for Google Workspace account security against advanced threats. Drive vulnerability research and adversarial simulation to expose novel account takeover techniques. Design and build advanced agentic systems and simulators to autonomously detect, analyze, and mitigate account security threats. Architect customer-facing agentic tools empowering Workspace and Cloud customers to proactively secure their environments. Investigate high-severity incidents and develop long-term mitigations. Requires 5+ years security engineering experience, coding proficiency, and preferred experience building AI agents and agentic workflows for security automation.

• AI Red Teaming
• Detection & Response
• LLM Security

Build autonomous AI security agents that perform alert triage, secure code reviews, threat modeling, and vulnerability assessment. Design agent orchestration systems, implement agent security controls for sensitive enterprise data, and create infrastructure for high-trust deployments. Conduct security testing of AI agents and their runtime platform. Research and implement novel security patterns for AI agent systems. Requires 5+ years software engineering experience, strong Python skills, and expertise in autonomous systems, security principles, and full-stack security considerations.

• AI Red Teaming
• LLM Security
• MLSecOps

Founding technical leader for NVIDIA's AI Safety & Security Engineering team. Defines harness architecture and engineering standards for AI-powered vulnerability discovery, validation, and patching systems. Owns technical roadmap for safety-critical AI system design and testing. Bridges exploratory research to production-grade software engineering. Mentors founding engineers and establishes team culture around secure AI development. Requires 18+ years designing complex systems, deep experience with ML pipelines and distributed systems, proven ability to translate research into production, and security engineering background.

• AI Red Teaming
• MLSecOps
• Security Research

Develop validation and patch methods for AI-powered vulnerability-finding and patching tools. Establish techniques to confirm vulnerabilities are real and reachable, advance approaches for generating and verifying safe fixes, and define correctness and revalidation standards. Work with LLM-based coding and analysis agents to improve software security. Apply rigorous security judgment to vulnerability classes affecting internal targets, ensuring fixes repair flaws, preserve behavior, and withstand strict revalidation. Maintain disciplined skepticism about AI-assisted tool outputs while leveraging them for analysis and development.

• AI Red Teaming
• LLM Security
• Security Research

Senior hands-on security engineer securing enterprise AI products at Cohere. Leads security reviews of AI-powered systems, threat models agentic capabilities, performs vulnerability testing and proof-of-concept development for AI-specific risks including prompt injection, unsafe tool use, identity/delegation failures, and tenant isolation. Builds secure defaults and scalable guardrails for AI systems. Requires strong software engineering fundamentals (Python, Go, TypeScript), experience leading security reviews for complex systems, and understanding of modern application architecture. Direct AI/agent security experience valued.

• Application Security
• Detection & Response
• LLM Security

Principal engineer role focused on defining and building core agentic identity and security capabilities for trusted AI agents at NVIDIA. Responsibilities include architecting agent identity security features across cloud and on-premises environments, prototyping solutions for credential brokering and workload identity, building reusable APIs and tooling for secure agent workflows, and applying adversarial thinking to security architecture decisions. Requires 15+ years in software engineering and security with hands-on technical leadership experience.

• Governance & Compliance
• LLM Security
• MLSecOps

Principal engineer role focused on designing and building core agentic identity and security capabilities at NVIDIA. Responsibilities include architecting agent identity features for cloud and hybrid environments, prototyping secure credential brokering and token exchange mechanisms, building reusable security APIs and tools, and evaluating emerging agentic identity standards. Requires 15+ years in security/identity engineering with hands-on technical leadership, strong offensive security and red teaming background, and expertise in AI-specific security risks including prompt injection and tool misuse.

• Governance & Compliance
• LLM Security
• Security Research

Conduct red team and penetration testing engagements against Anthropic's AI systems, cloud infrastructure, and deployments. Responsibilities include simulating advanced threat actors, testing specific high-value deployments, developing AI-assisted security testing tooling, and documenting findings for technical and executive audiences. Work cross-functionally on AI-specific attack scenarios. Requires 5+ years hands-on red teaming and offensive security experience, deep expertise in macOS/Linux/cloud security, strong vulnerability research and chaining skills, and Python/Go proficiency.

• AI Red Teaming
• Security Research

Design and build a secure platform for deploying and managing long-running autonomous agents at enterprise scale. Responsibilities include designing runtime safety harnesses with policy engines, approval gates, and kill switches; implementing credential brokering with least-privilege scoping; building observability and evaluation loops; ensuring secure multi-agent orchestration; and enabling self-improving agent systems through production telemetry. Work on threat modeling, authentication/authorization, secrets management, and incident response for agent fleets in production.

• Governance & Compliance
• MLSecOps

Design and build scalable ML infrastructure to support real-time safety deployments for Claude's ML-based safety classifiers and defenses. Develop monitoring and observability tools for classifier performance and data quality in safety-critical applications. Collaborate with research teams to productionize safety research into robust, scalable systems. Optimize inference latency and throughput for real-time safety evaluations. Implement automated testing, deployment, and rollback systems for ML models in production safety applications. Partner with Safeguards, Security, and Alignment teams to deliver infrastructure meeting safety and production needs.

• Detection & Response
• ML Engineering
• MLSecOps

Research Engineer combining ML and cybersecurity expertise to develop reinforcement learning environments and agentic systems for Anthropic's AI security infrastructure. Responsibilities include designing RL environments, conducting security experiments, implementing defensive solutions for incident response and vulnerability remediation, and collaborating with safety and security teams to advance AI system security.

• AI Red Teaming
• Detection & Response
• LLM Security

Research Engineer role at Anthropic focused on advancing AI security through reinforcement learning. Responsibilities include developing agentic integrations for autonomous security investigation and remediation, designing RL environments for incident response and vulnerability analysis, conducting security experiments and evaluations, and delivering solutions into production training runs. Requires ML experience combined with cybersecurity domain expertise, strong software engineering skills, and ability to balance research exploration with implementation. Experience in security engineering, detection and response, or applied defensive work is preferred.

• AI Red Teaming
• Detection & Response
• MLSecOps

Lead AI Security Architect for regulated enterprise. Secures AI adoption including LLMs, GenAI, RAG solutions and AI agents. Responsibilities include AI threat modelling, red teaming, prompt injection testing, designing security controls (AI gateways, prompt filtering, output sanitization), and integrating security into Agile/traditional delivery. Requires hands-on experience securing Azure OpenAI, AI Foundry, and GCP Vertex AI platforms. Engineering-led mindset with deep understanding of AI/ML and data platforms. Senior technical role requiring stakeholder engagement while remaining hands-on.

• AI Red Teaming
• LLM Security
• MLSecOps

Principal Security Researcher conducting cutting-edge security research on AI-powered DevSecOps platform. Responsibilities include developing novel testing methodologies for AI agent security, conducting hands-on penetration testing, validating vulnerabilities through proof-of-concept exploits, assessing AI attack vectors (prompt injection, agent manipulation, workflow exploitation), and leading security research into GitLab's AI and agentic surfaces. Will define security requirements for AI systems, build agent-assisted vulnerability discovery tooling, and mentor team members. Requires 10+ years security research/offensive security experience, strong coding proficiency, AI framework knowledge, and deep understanding of AI attack vectors.

• AI Red Teaming
• LLM Security
• Security Research

Staff Security Researcher conducting cutting-edge security research on GitLab's AI-powered DevSecOps capabilities, including Duo Agent Platform and GitLab Duo Chat. Responsibilities include identifying and validating vulnerabilities in AI and agentic surfaces, developing novel testing methodologies for AI agent security, conducting penetration testing, validating vulnerabilities through hands-on exploit development, and building automation for agent-assisted vulnerability discovery. Requires 7+ years in security research/penetration testing, expertise in multiple technical areas, proficiency in Ruby/Go/Python/TypeScript/Rust, and understanding of AI attack vectors including prompt injection and agent manipulation.

• AI Red Teaming
• LLM Security
• Security Research

Owns production infrastructure and operational deployment of Claude's safety systems. Responsibilities include configuring and verifying safeguards for model launches across all platforms (1P, AWS Bedrock, GCP Vertex), deploying new safety classifiers with canary rollouts, detecting configuration drift, leading incident response for safety issues, and automating launch and deployment processes. Requires deep production change management experience, high-stakes release leadership, on-call incident response background, and proficiency with cloud platforms and Python.

• Detection & Response
• LLM Security
• MLSecOps

NCSC AI Security Architect at GCHQ leading research on secure AI architecture design and systems. Responsibilities include designing secure architectures around AI technologies, collaborating on GenAI security research, assessing AI integration into existing and emerging systems, and developing secure frameworks and guidance for safe AI adoption. Work spans cloud platforms (AWS, Azure, GCP), identity and access management, AI agents, and hybrid cloud environments. Requires demonstrable expertise in technological vulnerabilities, security problem-solving, and modern technology systems.

• AI Red Teaming
• Governance & Compliance
• Security Research

Lead technical teams at MITRE's Trustworthy & Secure AI Department performing AI adversarial threat analysis and defense research. Assess threats to AI systems, develop mitigations against adversarial tactics, and integrate secure AI solutions into government systems. Requires 8+ years AI experience, hands-on expertise in agentic AI, deep learning, generative AI, and demonstrated AI red teaming or adversarial AI experience. Provide thought leadership on AI capabilities applied to cyber challenges and mentor technical staff. Active TS/SCI clearance required.

• AI Red Teaming
• MLSecOps
• Security Research

Lead and manage a high-performing security engineering team at Cohere focused on securing AI platforms and enterprise AI systems. Responsibilities include designing and implementing vulnerability management, SAST/DAST programs, leading penetration testing of web applications and agentic AI systems, managing bug bounty programs, and embedding security practices throughout the SDLC. Requires 8+ years of application security experience with expertise in vulnerability management, cloud security, and secure development practices.

• Application Security
• LLM Security
• MLSecOps

Deep Learning scientist/ML engineer developing safety for multi-modal LLMs and autonomous agents. Responsibilities include building datasets and evaluation algorithms for LLM security (backdoors, poisoning, latent behaviors), agentic safety (multi-turn tool-calling risks), and content safety. Work spans pre-training through post-training safety techniques, including filtering, RLHF/RLAIF, and novel detection approaches. Requires 8+ years ML engineering experience with 4+ years post-training and 1+ years dedicated AI safety expertise.

• AI Red Teaming
• LLM Security
• MLSecOps

Join AISI's Control Red Team to stress-test AI safety monitors at frontier labs. Design and execute adversarial attacks, ML experiments, and security evaluations to measure control measure efficacy. Conduct threat modeling and security analyses of deployment safeguards. Build tooling and experimental pipelines for rapid evaluation cycles. Combine research methodology with hands-on security testing to produce decision-relevant assessments for companies and government. Work with frontier model access and infrastructure support.

• AI Red Teaming
• Security Research

Join AISI's Misuse Red Team to develop and analyze attacks and protections for large language model systems. Lead technical direction or execution on red-teaming frontier AI safeguards, research novel attack vectors, develop automated attack tooling, and collaborate with frontier AI companies to identify and mitigate vulnerabilities. Contribute to advancing benchmarking of agent misuse, data poisoning defenses, and fine-tuning API security. Work with a team of experienced researchers from Anthropic, OpenAI, DeepMind, and top universities.

• AI Red Teaming
• LLM Security
• Security Research

Security Software Engineer supporting the operations and development of NVIDIA's AI-powered vulnerability management platform. Responsibilities include maintaining production scanning fleets powered by LLM agents, building full-stack features for the vulnerability hub, triaging and fixing issues, operating GitOps deployment pipelines, and collaborating on LLM agent harnesses that power automated security scanning across repositories and web applications. Requires Python, SQL, Linux fundamentals, and growing security expertise.

• Detection & Response
• LLM Security
• MLSecOps

Build and improve LLM-based red team agents for autonomous reconnaissance, exploitation, and evidence capture. Design multi-agent orchestration systems, encode operator tradecraft into prompts and tools, develop exploit-confirmation harnesses to reduce false positives, and engineer safety controls for autonomous offensive capability. Requires 12+ years security engineering with 4+ years offensive security (penetration testing, red teaming, exploit development), strong Python software engineering, practical LLM/agent framework experience, and hands-on exploitation skill in web applications, cloud/Kubernetes, or systems/binary domains.

• AI Red Teaming
• Security Research

Design and run evaluations measuring cyber-relevant capabilities and safeguarding robustness in AI models. Execute per-release robustness testing, analyze jailbreak and prompt-bypass data, and design detection probes for cyber abuse. Build internal tooling for running and scoring evaluations, and collaborate with policy and engineering teams to translate findings into safeguard improvements. Requires hands-on cybersecurity experience and Python proficiency.

• AI Red Teaming
• Detection & Response
• LLM Security

Lead multidisciplinary teams at RAND's Center on AI, Security and Technology to develop and execute systems that evaluate AI model vulnerabilities across attack lifecycles (initial access, lateral movement, defense evasion). Build benchmarks for autonomous AI operations in adversarial environments, including CTF frameworks and attack graph reasoning assessments. Design rigorous threat models and evaluation frameworks to assess AI stealth and adversarial capabilities. Communicate technical findings to senior government and industry leaders to inform responsible AI policy. Manage research budgets, complex technical projects, and lead cross-functional teams of engineers and researchers.

• AI Red Teaming
• MLSecOps
• Security Research

Senior AI Security Researcher at NVIDIA focused on developing methods, tools, and evaluations to test, attack, and defend frontier AI systems, agentic applications, and AI-enabled security automation. Responsibilities include discovering novel failure modes in AI models and autonomous agents, building rigorous evaluation harnesses, prototyping adversarial and defensive techniques, exploring LLM security, agent security, adversarial testing, model evaluation, and cyber-defense automation, and translating research into practical mitigations and secure-by-design recommendations for engineering teams.

• AI Red Teaming
• LLM Security
• Security Research

Lead RAND's AI Security Portfolio with oversight of 15+ researchers conducting technical research on securing advanced AI systems, cyber capability evaluation, and policy-informing analysis. Define research agenda on secure AI systems, manage cross-functional teams integrating technical R&D and cybersecurity operations, develop AI threat models and security architectures, and translate findings for policymakers and industry stakeholders.

• AI Red Teaming
• MLSecOps
• Security Research

Design, deploy, and evaluate AI-powered cybersecurity solutions within virtualized environments. Fine-tune NVIDIA Nemotron models for threat detection and automated response tasks. Build CI/CD pipelines for security product validation and benchmarking. Curate datasets for security analytics. Work at the intersection of AI development and cybersecurity with offensive security researchers to advance AI-powered defense capabilities.

• Detection & Response
• LLM Security
• MLSecOps

MITRE's Trustworthy & Secure AI Department seeks an AI Security Engineer to assess threats to AI systems, develop defenses against adversarial tactics, and integrate secure AI solutions into government systems. Responsibilities include adversarial threat analysis, vulnerability characterization in national security systems, MITRE ATLAS framework application, and capability innovation for cyber challenges. Requires Bachelor's degree plus 2 years AI experience (or advanced degree), advanced AI/ML theory knowledge, hands-on expertise in agentic AI or generative AI, Python proficiency, and ability to obtain TS/SCI clearance.

• AI Red Teaming
• MLSecOps
• Security Research

MITRE's Trustworthy & Secure AI Department seeks a Senior Adversarial AI Engineer to perform AI adversarial threat analysis, identify vulnerabilities in national security AI systems, and develop defenses against adversarial tactics. Responsibilities include threat assessment, vulnerability characterization, intelligence analysis and reporting, and technical subject matter expertise. Requires 5+ years AI experience with hands-on expertise in Generative AI, AI Security, Agentic AI, Testing & Evaluation, or Applied AI. Python and AI technical stack proficiency required. Active TS/SCI clearance mandatory.

• AI Red Teaming
• Security Research

Senior Manager leading Amazon's AI Red Team within Threat Operations. Builds and leads a team of security engineers conducting offensive security research and red team operations against AI systems, infrastructure, and emerging threats. Establishes AI offensive security research programs, oversees sophisticated red team operations targeting training pipelines and inference systems, and drives cross-organizational initiatives to assess AI-introduced vulnerabilities. Develops scalable offensive security automation and AI-augmented testing tools. Translates technical security findings into strategic recommendations for leadership. Requires 10+ years offensive security experience, 3+ years team management, and deep understanding of AI/ML security threats and adversarial machine learning.

• AI Red Teaming
• MLSecOps
• Security Research

Senior Solutions Architect designing and deploying secure agentic AI systems for enterprise. Responsibilities include architecting multi-agent workflows with guardrails and policy enforcement, integrating NVIDIA models into security detection and response products, building confidential AI deployments with GPU attestation and secure infrastructure, and creating reference architectures for production-ready secure AI. Requires 8+ years in AI/ML or enterprise software, hands-on LLM/agentic AI production experience, depth in AI/LLM security, confidential computing, or secure AI infrastructure, and knowledge of adversarial risks including prompt injection, jailbreaks, and supply-chain threats.

• LLM Security
• MLSecOps
• Security Research

Join Waabi's security team to establish AI security controls across the company. Audit AI tool usage, design layered guardrails and sandboxing patterns, maintain inventories of AI-to-service connections and their data access controls, partner with users to implement secure-by-default AI workflows, evaluate new AI tools and integrations, red-team security guardrails, and document guidance. Requires software development fundamentals, hands-on AI tool experience, core security knowledge, and familiarity with threat modeling and least privilege principles.

• LLM Security
• MLSecOps
• Security Research

Lead security engineering organization protecting AI-enabled cloud-native SaaS platform. Own application/product security, infrastructure/cloud security, and vulnerability management across distributed US and India teams. Design and implement security strategy for AI features including threat modeling, secure development standards, and AI-specific risk mitigation (prompt injection, agent permissions, model integrity). Drive vulnerability operations, cloud security posture, and secure SDLC practices. Balance strategic leadership with hands-on technical engagement to embed security into product delivery while maintaining compliance and customer trust.

• Application Security
• LLM Security
• MLSecOps

Build and maintain AI agents and infrastructure supporting NVIDIA's security organization, including agent-enabled workflows for certifications, risk, and compliance. Design and implement MCP integrations, ETL pipelines, and data infrastructure serving security agents. Requires 8+ years automation/data engineering experience, proficiency in Python/Go/C++, production AI/agent experience, and AWS/Terraform/Airflow expertise. Background in security or cybersecurity valued.

• AI Red Teaming
• Governance & Compliance
• MLSecOps

Amazon is hiring a Security Engineer for their AI Security team to design and validate security controls for AI/ML services including Amazon Bedrock, SageMaker, and generative AI platforms. The role involves analyzing security of AI/ML applications, discovering and addressing security issues, building security automation, threat modeling, penetration testing, and developing new testing methods. Responsibilities include secure SDLC practices, security reviews, tool development, and mentoring. Requires 2+ years in security vulnerabilities identification, scripting/programming, and system troubleshooting. This is a hands-on security engineering position focused on protecting enterprise-scale AI/ML services.

• LLM Security
• MLSecOps
• Security Research

Senior-level AI red team engineer role at Carnegie Mellon University's CERT Threat Analysis Directorate. Conducts adversary emulation exercises and red teaming against real-world AI-enabled systems in national security contexts. Responsibilities include developing offensive tactics and techniques for attacking AI systems, writing exploitation tools in Python, C, BASH, and PowerShell, reverse engineering AI platform components, and assessing security across hardware, software, and network layers. Requires 8+ years offensive security experience with penetration testing, red teaming, or exploit development background, proficiency with C&C frameworks, reverse engineering tools, and TCP/IP expertise. Position involves 25% travel and requires Department of War security clearance.

• AI Red Teaming
• MLSecOps
• Security Research

Senior technical leadership role at Lloyds Banking Group's Chief Security Office focused on designing and delivering secure engineering patterns, controls, and tooling for AI and ML systems. Responsibilities include securing model lifecycles and data pipelines, embedding DevSecOps practices, working with ML platforms (PyTorch, TensorFlow, MLflow, Kubeflow), cloud-native and containerised architectures, and building automation tooling. Direct involvement in code, automation, and platform design while influencing AI security strategy across the organization as it scales generative AI and agentic systems.

• LLM Security
• MLSecOps
• Security Research

AI Security Specialist at Lloyds Banking Group's Security Data & AI Lab. Protects AI design, build, and use across the organization. Responsibilities include embedding AI security strategy for safe adoption, assessing and strengthening security of AI platforms and applications, commissioning adversarial testing, designing AI-driven security capabilities (threat detection, anomaly detection, incident response), and advising on risk and compliance. Requires 5+ years cyber security experience including practical AI systems security, hands-on public cloud security engineering, understanding of AI/ML technologies, and security frameworks knowledge.

• AI Red Teaming
• LLM Security
• MLSecOps

Lead AI security strategy development at Siemens DI SW, reporting to the Chief Product Solution & Security Officer. Design and deploy security measures for AI models, data, and infrastructure. Develop security frameworks for AI systems and datasets. Conduct risk assessments and threat modeling to identify vulnerabilities. Lead research into adversarial attack detection and AI security defenses. Analyze AI security incidents and conduct forensic investigations. Develop tools to monitor AI security risks and detect anomalies in model behavior. Collaborate with AI researchers, software engineers, and security teams. Ensure compliance with NIST AI Risk Management frameworks and secure AI development guidelines.

• AI Red Teaming
• Detection & Response
• LLM Security

Support secure design, implementation, and adoption of AI systems across Lloyds Banking Group. Embed security controls in AI applications, support engineering teams with security validation and testing, ensure AI solutions meet security standards, and understand attacker exploitation of AI. Responsibilities include technical implementation of security controls, validation testing, and translating security requirements into actionable technical guidance for both technical and non-technical stakeholders.

• Detection & Response
• LLM Security
• MLSecOps

Lead engineer for NVIDIA's Agent Policy Fabric core platform, responsible for building runtime policy verification, signed policy bundle handling, trust-root management, policy projection, conformance testing, and cross-runtime integration for governed agentic systems. Design and harden authorization APIs, cryptographic verification pipelines, and fail-closed security defaults. Collaborate with runtime teams on public interfaces for policy enforcement, runtime attestation, and audit. Define versioning, latency budgets, and architecture specifications for product security and enterprise partner adoption.

• Governance & Compliance
• LLM Security
• Security Research

NVIDIA seeks an AI red teamer to reduce risk and threats in networking AI products. Responsibilities include hands-on safety and security research on AI/networking systems, developing tools to expose model and infrastructure vulnerabilities, defining AI development security standards, and partnering across teams. Requires 5+ years in AI safety/security and offensive cybersecurity, expertise in LLMs/generative AI/agents/RAG, Python programming, and MLOps knowledge (Docker, Kubernetes). Strong candidates have software product design experience and familiarity with PyTorch/TensorRT.

• AI Red Teaming
• LLM Security
• Security Research

Design, build, and deploy AI agent systems for enterprise security workflows including PQC transition, threat modeling, and automated mitigation. Architect LLM and RAG integrations with security data sources. Own full lifecycle from architecture through productization and operational deployment. Requires 5+ years experience with agentic systems, LLM production deployments, strong cryptography and secure design foundation, and Python system design expertise.

• AI Red Teaming
• LLM Security
• MLSecOps

Red team AI-enabled systems used in national-security contexts, combining offensive cyber tradecraft with AI security expertise. Develop attack tactics, techniques, and procedures against AI systems and their supporting infrastructure. Conduct adversary emulation exercises, write exploitation tools, and prepare defenders against real-world AI threats. Requires proficiency in penetration testing, exploit development, reverse engineering, C2 frameworks, and programming in Python, C, and BASH.

• AI Red Teaming
• Security Research

Red team AI-enabled systems used in national security contexts, combining offensive cyber tradecraft with AI security expertise. Develop tactics, techniques, and procedures for attacking AI systems and supporting infrastructure. Write tools in Python, PowerShell, C, and BASH. Conduct adversary emulation exercises, reverse engineering, vulnerability analysis, and real-world testing of AI platforms. Requires penetration testing, exploit development, and command-and-control framework experience.

• AI Red Teaming
• MLSecOps
• Security Research

Build trusted AI agents that augment security analyst judgment and automate detection, investigation, and response workflows. Develop context-aware agents analyzing security telemetry, design security-specific evaluations and benchmarks, optimize models and agents using production traces and analyst feedback, and take capabilities from experimentation through evaluation to production deployment. Provide technical direction for agentic AI initiatives and influence architecture decisions.

• AI Red Teaming
• Detection & Response
• LLM Security

Senior Data Scientist in NVIDIA's Security and Networking Architecture group developing agentic AI systems for automated threat analysis and response workflows. Responsibilities include building and optimizing generative models with RAG and tool-augmented reasoning, fine-tuning models for production security systems, developing ML algorithms across multiple data types, creating domain-specific security datasets, and benchmarking system performance. Requires MS/PhD, 5+ years production ML/DL experience, expertise with PyTorch/TensorFlow, agentic AI frameworks, LLM fine-tuning, and inference optimization. Security and networking background preferred.

• Detection & Response
• LLM Security
• ML Engineering

Staff-level engineer building secure and scalable systems for AI application and agent adoption at scale. Responsible for technical direction and architecture of AI security products, defining standards for secure systems, identifying architectural gaps, and leading high-impact initiatives spanning multiple teams. Requires 5+ years software engineering with systems and security expertise, proficiency in Go/Rust/Python, and hands-on execution including coding, design review, and debugging.

• LLM Security
• MLSecOps
• Security Research

Research position at Carnegie Mellon University's CERT Division focused on AI security. Responsibilities include vulnerability discovery and assessments for AI systems, reverse engineering AI models, evaluating effectiveness of AI system defenses, and identifying emerging threats. Work involves developing analysis approaches for AI system robustness, studying the AI security ecosystem, and publishing research findings for government and industry sponsors.

• AI Red Teaming
• MLSecOps
• Security Research

Conduct AI security research at Carnegie Mellon's CERT/SEI, focusing on vulnerability discovery, AI system robustness analysis, and defense evaluation. Reverse engineer AI systems, develop analysis methodologies and tools, study AI security ecosystems, and publish findings to influence national AI security strategy. Collaborate with cybersecurity experts, government officials, and industry practitioners on threat modeling, assessment frameworks, and emerging AI security challenges.

• MLSecOps
• Security Research

Conducts research into vulnerabilities and defenses of AI/ML algorithms within the Secure AI Lab. Responsibilities include counter AI research to identify threat models and weak points in AI systems, designing novel attacks and defenses, and advancing adversarial machine learning. Leads research projects, develops prototype capabilities for government customers, mentors junior researchers, and publishes original research on AI algorithm vulnerabilities and security mitigations.

• AI Red Teaming
• MLSecOps
• Security Research

Software engineer building data platforms and pipelines that power AI safety and oversight mechanisms. Responsibilities include designing data foundations for misuse detection and prevention systems, implementing governance and access controls for sensitive data, and operating infrastructure across multiple cloud providers. Focuses on correctness, retention discipline, and portability to support Anthropic's Safeguards team in monitoring models and preventing misuse.

• Detection & Response
• MLSecOps

AI Security Engineer joining a red team to lead end-to-end AI security assessment engagements with enterprise clients. Responsibilities include conducting comprehensive security assessments of LLM applications and multimodal agentic systems, developing novel red teaming methodologies, creating security testing frameworks, and building automation tooling. Requires 3+ years cybersecurity experience with red teaming focus, deep understanding of LLM vulnerabilities (prompt injection, data poisoning, jailbreaking), practical threat modeling, and proven ability to lead client-facing security projects. Research and innovation component involves translating academic AI security research into practical testing approaches for emerging modalities.

• AI Red Teaming
• LLM Security
• Security Research

Remote role at Mercor focused on red-teaming conversational AI models. Responsibilities include diagnosing vulnerabilities, annotating model failures, and generating actionable adversarial data to improve AI system safety. Requires hands-on adversarial testing experience and technical understanding of AI safety principles.

• AI Red Teaming
• LLM Security

Build and maintain the harness and platform infrastructure for NVIDIA's AI Safety & Security Engineering team that develops AI-powered tooling to find, validate, and patch software vulnerabilities. Design agent harness systems, evaluation infrastructure for running security research experiments, and reproducibility tooling. Partner with security researchers and evaluation engineers to support AI-driven vulnerability detection and validation workflows. Requires 5+ years software engineering experience, strong Python skills, and familiarity with agent frameworks, LLM orchestration, or ML infrastructure.

• AI Red Teaming
• MLSecOps
• Security Research

Capabilities researcher building Claude Security, responsible for identifying which security capabilities in frontier models are production-ready, measuring their performance on realistic cybersecurity tasks, and designing scaffolding to make them usable by non-expert security teams. Work includes rapid prototyping, rigorous evaluations, dataset and harness development for cybersecurity domains, and collaboration with engineers to operationalize capabilities. Requires 7+ years security research or engineering expertise in areas like vulnerability research, exploit development, malware analysis, or incident response, plus AI evaluation and red teaming experience.

• AI Red Teaming
• LLM Security
• Security Research

Experienced AI Security Engineer securing AI and GenAI solutions across an international organization. Key responsibilities include implementing AI-specific security controls, protecting against prompt injection and adversarial attacks, designing LLM security guardrails, conducting AI security assessments, threat modeling, and establishing secure AI development and deployment practices. Requires 3-5 years security engineering experience and 2+ years hands-on AI/ML security background with cloud environment knowledge.

• LLM Security
• MLSecOps
• Security Research

Expression of interest for technical AI researchers and engineers to develop foundations for agentic controls and forensics. Work focuses on building technical approaches to detect and understand misbehaviour from future generations of highly capable AI agents, with relevance extending beyond current systems.

• MLSecOps
• Security Research

Lead AI security program for healthcare tech platform. Design multi-layer AI security framework spanning data classification, detection, governance, and adversarial testing. Execute red-team assessments against AI applications and agentic workflows. Architect secure MCP server deployments and agent authentication standards. Perform adversarial testing for privilege escalation and tool misuse. Integrate AI security controls into CI/CD pipelines. Develop automated testing for AI systems and pipelines. Requires 7+ years security engineering, hands-on adversarial AI techniques, NIST AI RMF/ISO 42001 knowledge, and Python/GitHub skills.

• AI Red Teaming
• LLM Security
• MLSecOps

Staff-level backend engineer building lightweight security components for a Generative AI Security platform. Responsibilities include optimizing security sensors for minimal footprint across endpoints, browsers, and production workloads; designing adaptive AISPM policy logic; developing endpoint security solutions with real-time threat detection and data protection; and collaborating with security and product teams. Requires 4+ years Python/Node.js experience, macOS/Windows endpoint security expertise, OS architecture proficiency, and browser extension development skills. Focus on protecting organizations from GenAI risks while enabling safe AI innovation.

• Detection & Response
• LLM Security
• MLSecOps

Researcher at Carnegie Mellon University's CERT Division focused on AI security. Conducts vulnerability discovery, reverse engineering of AI systems and models, evaluates robustness of AI defenses, develops threat analysis methodologies, and influences national AI security strategy. Requires BS with 8 years, MS with 5 years, or PhD with 2 years experience in ML, cybersecurity, or related fields, plus practical experience in vulnerability research, reverse engineering, and AI/ML implementation.

• Detection & Response
• ML Engineering
• Security Research

Build secure, reproducible infrastructure and tooling for AI security evaluations at 10a Labs. Design cloud-based environments, automation, and tooling supporting scalable adversarial testing of AI systems. Develop and automate attack simulations to validate security controls and improve resilience of AI-powered systems. Conduct threat modeling and security design reviews. Collaborate with red teamers to reproduce and remediate vulnerabilities uncovered during AI security assessments. Requires 3–5 years security/software engineering experience, hands-on offensive security work, Python, AWS/GCP, infrastructure-as-code, and familiarity with LLMs and AI security.

• AI Red Teaming
• MLSecOps
• Security Research

Own the security of AI adoption across the enterprise. Review and assess AI system integrations (LLMs, RAG, APIs, automation tools), conduct threat modelling, and develop AI-specific guardrails. Identify and mitigate prompt injection, model poisoning, data leakage, and adversarial attacks. Design data protection controls for AI contexts and DLP policies. Lead shadow AI governance, third-party AI tool due diligence, and compliance mapping against EU AI Act, NIST AI RMF, ISO/IEC 42001, and financial regulations. Author AI security policies, maintain AI risk registers, and report to management and auditors.

• Governance & Compliance
• LLM Security
• MLSecOps

Design and build benchmarking and evaluation infrastructure for AI-powered security tooling at NVIDIA's AI Safety & Security Engineering team. Responsibilities include creating metrics and protocols to measure AI system effectiveness in vulnerability detection, designing reproducible experiments, mapping results to code and runs, and automating measurement infrastructure. Work directly with security researchers to evaluate agent and LLM behavior in security contexts.

• MLSecOps
• Security Research

Lead and build the foundational AI Safety & Security Engineering team at NVIDIA. Own delivery of vulnerability finding, validation, and patching systems powered by AI. Hire and mentor engineers across security research, harness engineering, and platform engineering disciplines. Drive technical roadmap execution, architect trade-offs in ML-based security tooling, and communicate engineering progress across the organization. Requires 12+ years software engineering experience with 5+ years managing complex systems teams.

• Detection & Response
• ML Engineering
• Security Research

Lead enterprise security strategy and architecture for AI-powered systems and Azure cloud environments. Establish security controls and runtime protections for agentic AI workflows. Conduct threat modeling for AI systems and cloud workloads, identifying risks from adversarial inputs and autonomous agents. Evaluate AI-generated code for security and define secure code review standards. Architect monitoring and hardening capabilities for AI agents at scale using Microsoft Defender and Sentinel. Embed security governance into AI/ML development pipelines and DevSecOps workflows. Research emerging AI and cloud security threats and translate insights into enterprise security improvements. Mentor teams on secure AI adoption and cloud security best practices.

• AI Red Teaming
• MLSecOps
• Security Research

Design and build automation pipelines for AI-driven security detection, investigation, and response. Operate SOAR playbooks and agentic AI workflows that triage and respond to security alerts with minimal human intervention. Develop integrations between security tools and AI inference services. Instrument automation pipelines with observability and run purple-team exercises to validate AI-driven responses under adversarial conditions. Collaborate with detection engineers, threat analysts, and AI/ML engineers to embed security automation into infrastructure workflows.

• AI Red Teaming
• Detection & Response
• MLSecOps

AI Security Researcher at Carnegie Mellon University's Software Engineering Institute (CERT Division). Develops approaches for analyzing robustness and vulnerabilities in AI systems. Responsibilities include reverse engineering AI models and malicious code, vulnerability discovery and assessment, designing analysis tools and methodologies, evaluating effectiveness of AI security defenses, and conducting research on AI security threats and mitigations. Requires BS with 8 years, MS with 5 years, or PhD with 2 years in ML, cybersecurity, or related discipline. Requires practical vulnerability research experience, familiarity with AI/ML frameworks (PyTorch, TensorFlow, NumPy), reverse engineering tools, and programming proficiency.

• AI Red Teaming
• MLSecOps
• Security Research

CERT Division researcher at Carnegie Mellon University focused on AI system security. Responsibilities include vulnerability discovery and assessment in AI systems, evaluating robustness of AI defenses, reverse engineering AI models, developing state-of-art analysis approaches, and shaping AI security best practices. Works with government sponsors, industry partners, and academic researchers. Requires 5+ years experience with PhDs, 8+ years with MS, or 10+ years with BS in ML/cybersecurity fields, plus proven expertise in both cybersecurity vulnerability research and practical AI/ML implementation.

• AI Red Teaming
• MLSecOps
• Security Research

Senior researcher at Carnegie Mellon's CERT Division focused on AI security. Responsibilities include developing approaches for analyzing robustness of AI systems, discovering vulnerabilities, reverse engineering AI models, evaluating defense effectiveness, and developing analysis tools and methodologies. Works on vulnerability assessments, threat characterization, and security research with government sponsors. Requires 10+ years experience (BS) or 8+ (MS) or 5+ (PhD) in ML/cybersecurity with practical vulnerability research, AI/ML implementation experience, familiarity with ML tools (PyTorch, TensorFlow, ART) and reverse engineering tools, and strong technical communication skills.

• AI Red Teaming
• MLSecOps
• Security Research

Lead a high-performing security engineering team at Isomorphic Labs, a frontier AI drug-discovery company. Own the technical security roadmap for AI-driven digital biology platforms, including ML pipeline security, model protection, autonomous workflow guardrails, and cloud infrastructure security. Translate complex scientific and business objectives into enterprise-grade security architecture while enabling velocity for ML researchers. Partner with the CISO on strategic initiatives spanning IAM, cloud security, secure SDLC, and security monitoring. Oversee incident escalation and vulnerability remediation for AI systems.

• LLM Security
• MLSecOps
• Security Research

Detect, investigate, and contain risk across AI tools, agents, and models. Monitor enterprise AI usage end-to-end for shadow AI and rogue agent activity. Investigate autonomous agent alerts, monitor AI data exfiltration via DLP, govern developer AI tool usage, and tune AI-specific detection rules. Support ISO 42001 audits and EU AI Act readiness. Requires 3-5+ years security analysis/SOC experience and demonstrated hands-on expertise in AI/LLM risk testing, CASB-based shadow AI discovery, non-human identity investigation, or agentic AI architecture security.

• Detection & Response
• LLM Security
• MLSecOps

Lead security frameworks and libraries for AI model development at Anthropic. Design and own cryptographic frameworks, secure serialization, and authorization systems that enable secure handling of model weights, training data, and customer data. Manage and grow a security engineering team, partner across product and infrastructure teams, conduct threat modeling and risk assessment, and drive framework adoption across the organization. Requires 3+ years managing security teams and 5+ years hands-on security engineering experience with deep expertise in securing complex architectures.

• Governance & Compliance
• MLSecOps
• Security Research

Red Team Engineer at Anthropic's Safeguards team conducting comprehensive adversarial testing of AI systems and products. Responsibilities include designing creative attack scenarios combining multiple exploitation techniques, researching novel testing approaches for agent systems and tool use, executing full kill-chain attacks simulating real-world threat actors, developing automated testing frameworks for continuous assessment, and translating security findings into product improvements. Requires penetration testing, red teaming, application security, model jailbreaking expertise, and hands-on experience with security testing tools and LLM-specific testing frameworks.

• AI Red Teaming
• LLM Security
• Security Research

Staff-level application security engineer leading M&A security due diligence and post-acquisition integration at Anthropic. Responsibilities include pre-close threat modeling and risk assessment, post-close SAST/DAST implementation, vulnerability remediation tracking, and coordinating cross-functional security integration. Role combines hands-on AppSec work (code review, threat modeling, penetration testing coordination) with AI-specific security focus, including securing agentic systems and LLM-integrated product surfaces. Develops automation tooling using LLMs to scale due diligence processes. Active participant in on-run incident response rotation and core AppSec projects.

• AI Red Teaming
• Application Security
• LLM Security

Security engineering role focused on protecting frontier AI evaluation infrastructure and models. Responsibilities include offensive security and automated AI red teaming against internal systems, building AI-powered detection and response systems for threats from agents and attackers, blue-team engineering including detection pipelines and incident response, and securing unique attack surface of pre-deployment model evaluations. Requires deep security expertise (systems, networks, cloud, identity), offensive security experience, and AI/LLM engineering skills with AWS proficiency.

• AI Red Teaming
• Detection & Response
• MLSecOps

Senior AI Security Engineer at Isomorphic Labs focusing on securing frontier AI-powered drug discovery systems. Responsibilities include adversarial threat modeling tailored to AI/ML vulnerabilities, establishing protection frameworks for ML model artifacts, designing guardrails and sandboxing for LLM ecosystems and autonomous agentic workflows, collaborating on ML lifecycle security controls from training through inference, leading AI security incident response with machine learning-driven threat hunting, and automating compliance monitoring against emerging AI regulations. Requires deep understanding of ML frameworks, cloud infrastructure security, adversarial ML threat vectors, agentic framework security, production-grade security tooling development, and pragmatic risk assessment balancing rigorous security with research velocity.

• AI Red Teaming
• Detection & Response
• LLM Security

Applied Security Researcher investigating AI, cloud, and code technologies to unlock new security features at Wiz. Conduct threat modeling and attack vector research for AI-native architectures. Design and implement agentic workflows for contextual understanding of cloud and application environments. Build functional prototypes and PoCs. Requires 5+ years security research experience, cloud security background preferred, with specialized AI security focus and model evaluation knowledge.

• AI Red Teaming
• LLM Security
• Security Research

Staff-level individual contributor driving technical strategy for application security across global product landscape. Responsibilities include threat modeling, vulnerability management at scale, DevSecOps automation, and pioneering AI-driven security automation using LLMs for code analysis and triage. Requires deep application security expertise, hands-on coding proficiency in modern languages, working knowledge of AI security frameworks, and ability to implement automated security guardrails that scale engineering velocity while maintaining security posture.

• Application Security
• LLM Security
• MLSecOps

Develop machine learning-based prototypes, tools, and systems for AI security applications at Carnegie Mellon University's CERT Division. Collaborate with researchers to design and execute experimental AI security solutions, including AI red teaming and adversarial ML initiatives. Support processing and analysis of large cybersecurity datasets, apply software engineering best practices to build scalable systems, and translate security research concepts into practical operational capabilities. Work alongside elite AI and cybersecurity professionals on national security-relevant AI security challenges.

• AI Red Teaming
• MLSecOps
• Security Research

AI Security Engineer advising on design, implementation, and security of generative AI solutions. Responsibilities include assessing AI/ML system security posture, leading threat modeling for LLMs and agentic systems, evaluating data security controls in RAG architectures, guiding secure SaaS AI integration, and developing AI security strategies. Requires 5+ years security engineering experience with hands-on enterprise agentic AI implementation, proficiency in Python, and deep knowledge of LLM-specific attacks including prompt injection and data poisoning.

• AI Red Teaming
• LLM Security
• MLSecOps

Senior ML researcher specializing in AI/ML algorithm vulnerabilities and defenses. Leads research in counter-AI threat modeling, adversarial machine learning, and defensive techniques. Develops and transitions security capabilities for government sponsors. Conducts original research in algorithm vulnerabilities, identifies attack vectors, designs novel mitigations, and evaluates defensive effectiveness. Mentors team members and collaborates on strategy for AI security research agenda.

• AI Red Teaming
• ML Engineering
• Security Research

Design and implement safeguards for internal AI usage, focusing on agentic systems, developer protection, and runtime security. Architect guardrails for tool-using AI systems including tool access controls, context isolation, and step-level validation. Build runtime enforcement mechanisms (interceptors, proxies, middleware) governing AI behavior at execution time. Design identity and access controls for non-human agents with short-lived credentials and scoped permissions. Implement logging and detection for AI activity including behavioral baselining and anomaly detection. Perform threat modeling using MAESTRO to identify attack paths and translate findings into practical safeguards. Protect developers using AI tools by preventing sensitive data exposure and validating AI-generated code.

• Detection & Response
• LLM Security
• MLSecOps

Lead Anthropic's Security Risk function, responsible for identifying, prioritizing, and treating complex security risks through AI-native platforms and automation. Design and build risk tooling powered by Claude for classification, triage, and continuous risk landscape sensing. Conduct threat modeling and risk quantification across identity, secrets, infrastructure, and supply chain security. Partner with Security Engineering to drive remediation roadmaps and build risk engineering culture. Mentor engineers across the organization on risk assessment and ownership. Requires 8+ years of security/software engineering experience with demonstrated ability to own complex security problems end-to-end.

• Detection & Response
• LLM Security
• MLSecOps

Red Teaming Fellow conducting adversarial testing of frontier AI systems and models. Responsibilities include designing and executing red teaming exercises to identify vulnerabilities and failure modes, developing attack strategies and test cases, analyzing model behavior under challenging conditions, documenting findings, supporting evaluation framework development, and researching emerging AI threats and attack techniques.

• AI Red Teaming
• Security Research

Design and build ML systems for AI safety and model evaluation at 10a Labs. Develop evaluation pipelines, benchmarks, and metrics for frontier AI systems. Run ML experiments to assess capabilities, robustness, and limitations of advanced AI systems including LLMs and multimodal models. Train, fine-tune, and evaluate models; identify failure modes and security risks. Work with reinforcement learning, NLP, computer vision, and agentic AI fundamentals. Requires 3–5+ years ML experience, strong Python and PyTorch/JAX skills, experimental design expertise, and familiarity with adversarial evaluations and AI agent security risks.

• AI Red Teaming
• ML Engineering
• MLSecOps

Design and execute red team assessments against AI systems and applications. Develop adversarial testing methodologies to evaluate system security and robustness. Craft prompts, attack chains, and adversarial inputs to uncover unsafe behavior. Identify vulnerabilities and failure modes through offensive testing. Analyze system outputs to assess security and safety risks. Collaborate with engineers and researchers to improve system security. Requires 2–5 years of cybersecurity experience, proficiency with security tools (Splunk, Burp Suite, Metasploit, etc.), scripting capability, and familiarity with AI/ML attack vectors including prompt injection and jailbreak techniques.

• AI Red Teaming
• Application Security
• LLM Security

NVIDIA Networking's AI red teaming role focused on improving safety and security of AI models, systems, and infrastructure. Responsibilities include hands-on safety/security research, tool development to expose AI vulnerabilities, defining secure AI development processes, and partnering with cross-functional teams. Requires 5+ years in AI safety/security and offensive cybersecurity, Python expertise, and deep understanding of LLM, MLLM, generative AI, agents, and RAG workflows.

• AI Red Teaming
• LLM Security
• MLSecOps

Architect and implement core infrastructure for an AI Security plane protecting LLM and generative AI applications. Responsibilities include designing real-time threat detection, input/output sanitization, and guardrail execution frameworks; building resilient distributed systems using Rust and async/await; implementing gRPC services for integration with security infrastructure; and optimizing performance across LLM models and the full stack. Lead complex multi-functional projects defining technical roadmatics and driving cross-team execution. Requires 8+ years software engineering, deep Rust expertise, distributed systems design, and Linux internals knowledge. Preferred: experience with LLM threat detection, input sanitization, and guardrail frameworks.

• Detection & Response
• LLM Security
• MLSecOps

Expression of interest for red team positions at the UK AI Security Institute. Roles involve cutting-edge research to identify, evaluate, and stress-test vulnerabilities in frontier AI systems. Work spans three areas: Alignment (detecting misalignment and loss-of-control risks), Misuse (stress-testing safeguards and developing attack tooling), and Control (evaluating control measures using adversarial ML techniques). Findings inform AI companies (Anthropic, OpenAI, DeepMind) and UK/allied governments on deployment and policy.

• AI Red Teaming
• Security Research

Senior Security Researcher at SentinelOne's Detection AI Research team. Research attack techniques and TTPs using EDR telemetry from millions of endpoints. Design, build, and maintain AI-powered detection pipelines end-to-end that apply ML models and LLM-based agents to detect sophisticated attacks. Drive development of LLM agents that automate detection authoring. Analyze detection gaps and false positives with MDR analysts and threat hunters. Requires 5+ years in security research/threat hunting/detection engineering, deep Windows internals knowledge, SQL/KQL/EDR query skills, Python development, and experience applying ML/LLMs to security problems.

• Detection & Response
• LLM Security
• Security Research

Senior security engineer responsible for designing and maintaining secure CI/CD pipelines, establishing SSDLC practices, and implementing security best practices. Key responsibility includes assessing and mitigating risks from AI technologies, including LLM applications, AI agents, prompt injection, and model supply chains. Must evaluate and govern AI-powered development tools securely and ensure compliance with AI security frameworks. Requires 4+ years cybersecurity/DevSecOps experience and practical familiarity with AI tools and AI security best practices.

• Governance & Compliance
• LLM Security
• MLSecOps

Develop machine learning-based prototypes, tools, and systems for AI security applications. Support AI red teaming, adversarial ML initiatives, and security analysis of AI systems. Process and analyze cybersecurity datasets (malware, NetFlow, incident data). Collaborate with researchers to design and execute experimental AI security solutions. Translate research concepts into practical operational capabilities using software engineering best practices.

• AI Red Teaming
• ML Engineering
• Security Research

Develop machine learning-based prototypes, tools, and systems for AI security applications at CERT/SEI. Work on AI red teaming, adversarial machine learning, and generative AI security. Collaborate with researchers to design experimental AI security solutions, process large cybersecurity datasets (malware, NetFlow, incident data), and translate research concepts into operational capabilities. Support national security AI security strategy through software and ML engineering practices.

• AI Red Teaming
• MLSecOps
• Security Research

Develop machine learning-based prototypes, tools, and systems for AI security applications. Support AI red teaming, adversarial ML initiatives, and security analysis of AI systems including generative AI and LLMs. Process and analyze diverse cybersecurity datasets (malware, NetFlow, incident data) using ML and data analytics. Collaborate with elite AI and cybersecurity professionals to design and execute experimental AI security solutions and translate research concepts into practical operational capabilities.

• AI Red Teaming
• MLSecOps
• Security Research

Director of Evaluations at LawZero, a non-profit developing safe-by-design AI systems. Lead the Evaluations Team (8-10 people) to design and execute comprehensive safety, capability, and adversarial robustness evaluations of the Scientist AI and frontier LLMs. Establish evaluation strategy and roadmap; design novel benchmarks and datasets measuring safety properties (honesty, goal-directedness, explainability); lead red-teaming programs to test resistance to jailbreaks, prompt injection, and data poisoning; develop evaluation infrastructure and tooling; publish technical reports and model cards; represent LawZero on AI safety measurement with external safety institutes.

• AI Red Teaming
• LLM Security
• Security Research

Senior-level role at CERT/SEI developing machine learning-based prototypes, tools, and systems for AI security applications. Responsibilities include AI red teaming, adversarial machine learning research, security analysis of AI systems, and processing cybersecurity datasets. Work spans generative AI, large language models, and counter-AI applications. Requires BS+10yr, MS+8yr, or PhD+5yr in CS, ML, cybersecurity, or related fields. Demands security clearance and software engineering expertise with containerization and microservices.

• AI Red Teaming
• MLSecOps
• Security Research

Conduct deep technical research to discover novel risks and attack vectors in cloud- and AI-native environments. Work with Product and Engineering teams to identify unaddressed risks, deliver proofs of concept, and define foundational security capabilities. Requires 5+ years hands-on security research experience, proficiency in Python/Go scripting, and preferred expertise in AI security risks in enterprise deployment contexts.

• AI Red Teaming
• Security Research

Senior AI Security Engineer responsible for red teaming and penetration testing of generative AI implementations including LLMs, agents, chatbots, and coding assistants. Combines offensive testing (prompt injection, jailbreaking, data exfiltration, agent abuse) with defensive work (guardrails, input/output controls, system prompt hardening). Designs and operationalizes security controls based on OWASP Top 10 for LLM Applications and Agentic Applications. Develops automation tools for continuous LLM testing, documents findings with remediation playbooks, and collaborates with SOC on detection. Requires 4+ years in application security/penetration testing with hands-on LLM and generative AI attack/defense experience.

• AI Red Teaming
• Application Security
• LLM Security

Hands-on security architect/engineer building and securing agentic AI systems including agent runtimes, MCP servers, tool registries, and connectors. Responsibilities span implementing secure agent patterns (planner/executor, tool routing, RAG boundaries), threat modeling workflows for prompt injection and data exfiltration, enforcing schema validation and policy controls, and designing advanced guardrail architectures. Requires 8+ years production security engineering, strong coding in Python/TypeScript, practical experience integrating LLM APIs, and familiarity with agent frameworks like LangGraph or LangChain.

• AI Red Teaming
• LLM Security
• MLSecOps

Conduct AI security research at Carnegie Mellon's Software Engineering Institute (CERT Division). Develop approaches for analyzing robustness and identifying vulnerabilities in AI systems. Perform reverse engineering of AI systems and malicious code, evaluate effectiveness of AI security defenses, and design analysis tools and methodologies. Study AI security ecosystems, threat characterization, and disclosure practices. Collaborate with government, industry, and academic partners on AI security strategy. Requires BS in ML/cybersecurity/related field with 3+ years experience OR MS with 1+ year experience. Must have practical vulnerability research background, AI/ML implementation experience, familiarity with ML frameworks (PyTorch, TensorFlow, ART) and reverse engineering tools, and strong technical communication skills.

• MLSecOps
• Security Research

Hands-on Threat Intelligence Engineer responsible for detecting and countering nation-state and criminal threats targeting frontier AI development. Tracks adversaries, builds automated pipelines and tooling to operationalize indicators into detection and alerting stacks, conducts intelligence-driven threat hunts across endpoint/cloud/identity telemetry, performs technical malware and infrastructure analysis, authors detection rules, and partners with detection engineering and incident response teams. Requires 5+ years in cyber threat intelligence or intrusion analysis, deep knowledge of threat actors and tradecraft, strong Python engineering, malware analysis expertise, and detection logic authoring experience.

• Detection & Response
• Security Research

Hands-on security infrastructure engineer responsible for vulnerability management, SIEM/XDR detection engineering, incident response, and supply chain security across AWS and Kubernetes. Leads threat modeling, detection rule development, infrastructure hardening, CI/CD security, and container supply chain risk controls. Works directly with engineering teams to validate findings, drive remediation, and implement security automation including AI-enhanced tooling for detection and operations efficiency.

• Detection & Response
• MLSecOps

Engineering fellowship at AI safety and threat-intelligence company 10a Labs. Hands-on role combining applied research and engineering across red teaming, abuse detection, and AI system evaluation. Three concentrations available: Software Engineering (cloud infrastructure, testing, secure systems), Data Engineering (data sourcing, architecture, dashboards), or Machine Learning (model training, agentic systems, frontier model evaluation). Supports client-facing products and research initiatives in AI security and Trust & Safety.

• AI Red Teaming
• ML Engineering
• MLSecOps

Member of Technical Staff in Safety for Agents team at Cohere, focused on developing safer, more secure LLMs that access external resources and take actions. Responsibilities include designing data generation and post-training algorithms, creating evaluation methods for agent safety, analyzing dataset quality and biases, hands-on LLM training on distributed infrastructure, and collaborating with ML and product teams to improve model robustness and generalizability. Requires strong software engineering, statistical expertise, and ML research background.

• LLM Security
• ML Engineering
• MLSecOps

Research Scientist focused on agent robustness and AI safety. Responsibilities include researching AI agent capabilities with emphasis on safety and risk factors, designing harnesses to test agents' tendency to take harmful actions, creating exploits and mitigations for agent failure modes, and characterizing risks in multi-agent systems. Requires practical ML research experience, proficiency with post-training techniques (RLHF, DPO, GRPO), published research track record, and 3+ years addressing sophisticated ML problems. Red-teaming and adversarial testing experience valued.

• AI Red Teaming
• Security Research

Research Scientist role focused on AI controls and monitoring at Scale Labs. Responsibilities include designing real-time monitoring and observability methods for advanced AI models, researching layered control mechanisms including fail-safes and intervention protocols, conducting red-team simulations to identify gaps in oversight, and collaborating with policymakers and engineers on AI safety standards. Requires 3+ years ML experience, published research track record, and hands-on prototyping skills. Nice-to-haves include runtime monitoring, anomaly detection, alignment research, and post-training techniques like RLHF.

• AI Red Teaming
• MLSecOps
• Security Research

Lead Machine Learning team developing GenAI security models for threat detection and automated vulnerability assessment. Operationalize security research findings into production LLM-based detectors for prompt injection and GenAI threats. Fine-tune language models using LoRA/PEFT for multilingual security detection. Implement MLOps pipelines with data governance, model monitoring, and drift detection. Collaborate with security research and platform teams to integrate threat detection models into Vulcan's blue team (defensive) and red team (vulnerability assessment) capabilities. Prepare multimodal detection systems for visual/audio threats. Lead ML engineers and manage compute resources.

• AI Red Teaming
• LLM Security
• MLSecOps

Applied data scientist at 10a Labs focused on designing and automating adversarial red-teaming frameworks and evaluations for frontier AI systems. Responsibilities include developing evaluation frameworks, designing red-teaming strategies, leading adversarial testing initiatives (jailbreak simulation, evasion probes), automating workflows for model evaluation and AI experiments, fine-tuning LLMs for safety assessment, and coordinating with ML and infrastructure teams. Requires 3-5 years production ML experience with emphasis on model behavior analysis and safety evaluation.

• AI Red Teaming
• LLM Security
• MLSecOps

Staff-level security engineer responsible for designing and building complex security systems protecting Anthropic's AI infrastructure. Focus areas include identity and secrets management for model weights and training data, developer security and supply chain hardening, infrastructure security across multi-cloud environments, and secure cryptographic frameworks. Leads threat modeling efforts, mentors security engineers, and drives security ownership across the engineering organization. Requires 8+ years of software engineering with deep security expertise, strong systems programming skills, and experience with identity systems, cryptography, Kubernetes security, and large-scale infrastructure.

• MLSecOps
• Security Research

Lead Machine Learning team at AIFT developing GenAI security detection models. Responsibilities include: operationalizing threat detection techniques from security research into production ML models; fine-tuning LLMs for multilingual security intents; evaluating multimodal (text, image, audio) threat detection; optimizing ML pipelines and infrastructure; implementing data versioning and monitoring for model drift; collaborating with research and platform teams on model integration; and translating technical constraints to leadership. Requires 5+ years ML engineering experience, MLOps proficiency (MLflow, Kubeflow, Airflow, DVC), Python/Docker/Kubernetes expertise, and LLM/Transformer knowledge.

• LLM Security
• ML Engineering
• MLSecOps

LLM Security Evaluation Expert role at government solutions firm focused on rigorously testing security and integrity of Large Language Models. Responsibilities include designing sophisticated adversarial prompt attacks, testing model vulnerabilities, documenting security findings, and identifying model biases. Requires TS/SCI clearance and deep LLM knowledge combined with cybersecurity expertise. Emphasis on responsible adversarial testing practices to safeguard AI systems.

• AI Red Teaming
• LLM Security

Subject Matter Expert on AI security within Greenhouse's product security team. Responsibilities include securing emerging AI and Machine Learning features, improving security best practices across agile SDLC, collaborating with engineers to harden AI/ML systems, staying current on AI/ML security trends, and proactively identifying and mitigating risks before deployment.

• Application Security
• LLM Security

Build foundational systems for safety and oversight of AI models at Anthropic's Safeguards team. Develop infrastructure for detecting unwanted model behaviors, preventing misuse, and supporting human/agentic review. Create robust multi-layered defenses for real-time safety improvements and establish metrics and evaluation systems for AI system safeguards.

• Detection & Response
• LLM Security
• MLSecOps

Detect and investigate misuse of Anthropic's AI systems for cyber operations including malware development, social engineering, and influence operations. Develop abuse detection signals, create threat intelligence reports on LLM attack vectors, conduct cross-platform threat analysis, and implement systematic safety improvements. Build threat detection systems and maintain relationships with external threat intelligence partners.

• Detection & Response
• LLM Security
• Security Research

Build and ship Claude Security products that leverage frontier AI models for cybersecurity applications. Responsibilities include developing agent loops, tool integrations, and backend infrastructure for security products; collaborating with research teams to identify and develop new model capabilities for security use; and iterating based on user feedback. The role bridges research and go-to-market, requiring strong generalist engineering with technical depth in distributed systems, TypeScript, Python, or Go. Candidates with incident response, penetration testing, reverse engineering, or network analysis experience are preferred. This position requires 7+ years of software engineering experience.

• Application Security
• LLM Security
• MLSecOps

Offensive-focused security engineer role securing AI-enabled systems, agents, and LLM-integrated workflows across EA's games, services, and enterprise platforms. Responsibilities include adversarial testing of LLM systems for prompt injection, data leakage, authentication gaps, and abuse paths; assessment of agentic and multi-agent workflows for privilege escalation and unsafe action chaining; design and operation of AI-driven security agents and automation; development of tooling and validation frameworks; and translation of findings into secure design patterns. Requires strong application/offensive security background, hands-on exploitation experience, LLM/agent system testing expertise, and ability to build automation using Python, Go, or JavaScript.

• AI Red Teaming
• LLM Security
• MLSecOps

Join Cynet to build next-generation AI-powered cybersecurity products. Drive innovation by combining security research with modern AI techniques to develop intelligent generative AI agents for automated threat analysis and investigation workflows. Design and implement ML models for endpoint detection, extending an AI antivirus engine through feature engineering, file parsers, and model development. Serve as the cybersecurity expert within the Data Science team, guiding threat modeling and security-driven AI design. Engineer core components in C++ and Python, integrate into platform infrastructure, and run experiments using ML pipelines to deliver production-ready detection models.

• LLM Security
• MLSecOps
• Security Research

Security researcher responsible for proactively red teaming and hacking high-impact GenAI systems at Microsoft, including Bing Copilot, Security Copilot, Github Copilot, and Windows Copilot. Conducts adversarial machine learning research to find safety and security failures in AI models and applications pre-launch. Works with interdisciplinary teams of red teamers, ML researchers, and safety experts to identify and inform mitigations for AI security and trust risks.

• AI Red Teaming
• LLM Security
• Security Research

Lead cybersecurity incident response and detection efforts at Anthropic. Develop and deploy novel tooling leveraging Large Language Models to enhance detection, investigation, and response capabilities. Create detections, playbooks, and workflows to identify and respond to incidents across Anthropic's AI technology stack. Requires 3+ years software engineering with security experience, or 5+ years detection engineering/incident response/threat hunting experience. Python proficiency, cloud environments knowledge, and experience with EDR, SIEM, or SOAR tools preferred.

• Detection & Response
• LLM Security

Senior security consultant role focused on AI/ML security architecture and design. Responsibilities include defining enterprise AI/ML security strategy, designing secure AI/ML models and pipelines across cloud platforms, leading adversarial testing and risk assessments, and embedding ethical AI governance. Works with major government and enterprise clients on securing advanced AI/ML systems against adversarial threats and compliance challenges.

• AI Red Teaming
• LLM Security
• MLSecOps

Staff-level software engineer building safety and oversight mechanisms for AI systems at Anthropic. Responsibilities span three sub-teams: (1) Safeguards Acceleration—developing sandboxed agentic systems for abuse investigation and detection calibration with provenance guarantees; (2) Safeguards Interventions—building composable intervention systems that execute across detection signals for harmful content, acceptable use, and child safety; (3) Safeguards Data Intelligence—operating autonomous agent fleets for large-scale threat detection across cyberattacks, weapons development, and influence operations. Core work includes abuse detection infrastructure, real-time multi-layered defenses, prompt engineering and adversarial testing, distributed systems at scale, and integration with operational security teams.

• AI Red Teaming
• Detection & Response
• MLSecOps

Develop ML systems to detect and mitigate misuse of AI products at scale. Build classifiers for harmful behavior detection, systems to identify coordinated attacks, threat models for agentic risks, and mitigations for prompt injection. Conduct research on automated red-teaming and adversarial robustness. Requires 4+ years ML/research engineering experience, Python proficiency, and familiarity with language models, anomaly detection, or adversarial ML.

• AI Red Teaming
• Detection & Response
• LLM Security

Design and implement security frameworks for GitLab's internal AI systems, including LLMs and AI agents. Secure Model Context Protocol implementations, manage non-human identity systems with zero-trust access controls, govern internal AI tool usage through DLP and monitoring, and prevent data leakage through AI systems. Collaborate cross-functionally on AI security adoption and evaluation of enterprise AI tools.

• Governance & Compliance
• LLM Security
• MLSecOps

Design, build, and deploy AI-powered security agents for threat detection, incident analysis, and automated response. Develop agentic workflows that autonomously perform log forensics, threat hunting, and incident response tasks. Integrate agents with data lakes, SIEM platforms, and security toolstacks. Requires 5+ years professional experience with 3+ years in cybersecurity operations, hands-on incident response, Python proficiency, LLM/agentic framework experience, and cloud security knowledge.

• Detection & Response
• LLM Security

Conduct applied and theoretical research into GenAI vulnerabilities including adversarial attacks, prompt injection, jailbreaks, and data poisoning across multimodal systems. Develop AI security evaluation frameworks, datasets, and performance metrics. Design and evaluate mitigation strategies including fine-tuning, guardrails, and robust architectures. Publish findings in top-tier venues and integrate research into AI security products.

• AI Red Teaming
• LLM Security
• Security Research

Join the AI Safety Institute's Safeguard Analysis Team to research and develop interventions that secure frontier AI systems from abuse. Responsibilities include assessing security threats to advanced AI systems, developing novel attacks against LLMs, conducting red-teaming evaluations, and building infrastructure for running security assessments. The role spans research-oriented work (threat analysis, attack development) and engineering-oriented work (evaluation infrastructure). Candidates should have experience in AI security, computer security, machine learning, red-teaming, and proficiency with large language models and Python. Mentorship from world-class researchers including alumni from Anthropic, DeepMind, and OpenAI.

• AI Red Teaming
• LLM Security
• Security Research

Threat Detection Researcher at Wiz responsible for developing cloud-native threat detection capabilities. Drives the full lifecycle of security detections from research and data analysis to production deployment. Designs behavioral baselines for cloud environments, expands detection engine with novel telemetry sources, and conducts deep technical research into cloud services to uncover attack vectors. Investigates real-world attacks and hunts emerging threats targeting cloud ecosystems. Requires 6+ years hands-on security/threat research experience, Python/Go proficiency, and proven track record of delivering actionable security impact.

• Detection & Response
• Security Research

Join Wiz's Threat Research team to develop cloud-native threat detection capabilities. Drive the complete lifecycle of security detections from research and data analysis to production deployment. Design behavioral baselines for complex cloud environments, develop high-fidelity detections from diverse signals, and expand the detection engine with novel telemetry sources. Conduct deep technical research into cloud services to uncover attack vectors, investigate real-world attacks across cloud platforms and identity providers, and hunt emerging threats targeting the cloud ecosystem. Requires 6+ years of hands-on security/threat research experience, proficiency in Python, Go, and query languages, plus background in incident response, red teaming, or threat hunting.

• Detection & Response
• Security Research

Detect and respond to malicious uses and abuse of AI systems. Investigate threat actors and harmful behaviors through SQL and Python data analysis, OSINT cross-referencing, and detection pipeline development. Support incident escalations and provide investigative reports for frontier AI labs and platforms. On-call responsibilities for urgent security escalations.

• AI Red Teaming
• Detection & Response

Research Engineer on Alignment Science at Anthropic focused on exploratory experimental research on AI safety. Responsibilities include building and running ML experiments to understand and steer AI system behavior, testing robustness of safety techniques through adversarial model training, running multi-agent RL experiments, building tooling to evaluate LLM-generated jailbreaks, and contributing to alignment stress-testing and pre-deployment safety assessments. Work feeds into key safety efforts including the Responsible Scaling Policy and involves collaboration with Interpretability, Fine-Tuning, and Red Team colleagues.

• AI Red Teaming
• MLSecOps
• Security Research

Build and scale AI-powered security analytics infrastructure at Anthropic's Detection Platform team. Design scalable data pipelines for processing security telemetry, develop ML-powered detection systems, and create innovative solutions leveraging Claude for security operations. Responsibilities include architecting detection and incident response capabilities, implementing security data pipeline infrastructure, and leading cross-functional security initiatives. Requires 7+ years software engineering experience with focus on security and data pipelines, strong cloud infrastructure knowledge, and ability to apply ML/AI to security problems.

• Detection & Response
• MLSecOps
• Security Research

Prompt and AI Security Engineer responsible for designing and optimizing AI-generated prompts to prevent security vulnerabilities such as injection attacks and model manipulation. Customize and integrate AI security solutions with applications and ML models. Implement security protocols for AI model deployment, conduct security assessments to identify vulnerabilities, develop tools for prompt security testing, analyze real-world AI threats, and provide technical advisory to clients on secure AI implementation. Stay updated on LLM and NLP security trends.

• AI Red Teaming
• LLM Security
• MLSecOps

ML researcher focused on safety and security solutions for large language models and multimodal systems. Responsibilities include conducting original research on adversarial robustness, LLM interpretability, and secure training; developing techniques to mitigate LLM-specific risks like prompt injection and data leakage; designing and deploying production LLMs with integrated safety features; implementing monitoring tools for threat detection; identifying vulnerabilities and attack vectors; and building frameworks to evaluate LLM safety under operational scenarios. Collaborates with cross-functional teams and DevOps to integrate security outcomes into scalable LLM deployment workflows while ensuring compliance with safety and privacy regulations.

• AI Red Teaming
• Detection & Response
• LLM Security

Staff-level application security engineer responsible for designing and operating LLM-driven security systems at Anthropic, including AI-assisted code analysis, vulnerability remediation, and threat modeling. Leads secure design reviews for agentic and LLM-integrated systems, manages bug bounty programs with AI automation, and responds to security incidents on Claude production systems. Requires 7+ years in application security with hands-on coding (Python, Go, Rust, TypeScript), threat modeling expertise, and experience with LLM systems or code-execution environments.

• Application Security
• LLM Security
• MLSecOps

Application Security Engineer at xAI responsible for securing cloud-native applications and AI systems. Conduct code reviews, implement secure coding guidelines, integrate security in CI/CD pipelines, perform threat modeling, and manage vulnerability remediation. Address AI/ML-specific security concerns including OWASP LLM Top 10. Evaluate software supply chains and SBOMs. Support incident response and stay current on emerging threats in cloud-native and AI technologies.

• Application Security
• LLM Security
• MLSecOps

Conduct in-depth research on AI-specific security threats including adversarial attacks, model tampering, and data privacy issues. Develop and implement strategies to detect and mitigate AI security vulnerabilities in NLP, computer vision, and other ML domains. Collaborate with cross-functional teams to integrate AI security measures into products and stay current with AI security research trends. Requires 5+ years AI/ML experience with demonstrated security research publications and hands-on experience deploying secure AI systems.

• AI Red Teaming
• MLSecOps
• Security Research

ByteDance seeks an AI Security Researcher to conduct research and analysis of security threats to AI technology. Responsibilities include identifying vulnerabilities in AI systems, developing countermeasures, conducting penetration testing and risk assessments, monitoring system security, developing security protocols, analyzing potential security incidents, and collaborating with cross-functional teams to implement security measures. The role requires expertise in AI security with focus on safeguarding cutting-edge AI systems and staying current with industry threats and compliance standards.

• Detection & Response
• Security Research

ML Research Engineer role focused on applied AI safety and reliability for government applications. Responsibilities include designing reliable agentic systems, conducting systemic red-teaming and evaluation, developing safety benchmarks, mitigating hallucinations in regulated environments, and optimizing models for high-stakes use cases. Requires Python proficiency, LLM benchmarking experience, evaluation expertise, and ability to bridge research concepts with production systems for sovereign AI applications.

• AI Red Teaming
• Detection & Response
• LLM Security

Security engineer specializing in red teaming and penetration testing for Cymetrics, a cybersecurity SaaS platform provider. Responsibilities include planning and executing red team exercises, conducting penetration tests across modern web frameworks (React, Angular, Vue.js), performing lateral movement and network reconnaissance, researching vulnerabilities in websites and open-source projects, assisting with automated security tool development, and collaborating on proprietary security product improvements. Requires 3+ years red teaming experience, expertise in OWASP methodologies, web vulnerability assessment, and client communication. The role supports a comprehensive security assessment SaaS platform that includes AI model vulnerability verification.

• AI Red Teaming
• Application Security
• Security Research