Research Engineer, Frontier Red Team (Autonomy)

Our team is focused on a critical question: how do we defend against a world where powerful, autonomous, self-improving AI systems may be used adversarially?

As a Research Engineer on our team, you'll build and eval model organisms of autonomous systems and develop the defensive agents needed to counter them. This work sits at the intersection of AI capabilities research, security, and policy—what we learn directly shapes how Anthropic and the world prepare for advanced AI.

This is applied research with real-world stakes. Your work will inform decisions at the highest levels of the company, contribute to public demonstrations that shape policy discourse, and help build technical defenses that could matter enormously as AI systems become more capable.

What You'll Do

• Design and build autonomous AI systems that can use tools and operate across diverse environments—creating model organisms that help us understand and defend against advanced adversarial AI
• Create evals and training environments to understand and shape agent behavior in desirable ways
• Develop defensive agents that can detect, disrupt, or outcompete adversarial AI systems in realistic scenarios
• Interface Claude with hardware platforms (e.g. robotics, physical systems) to understand cyberphysical risks and defenses
• Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public
• Collaborate with external experts in cybersecurity, national security, and AI safety to scope and validate research directions

Sample Projects

• Developing systems where Claude controls diverse hardware and robotics platforms simultaneously
• Creating attack-defend simulations (CTFs, wargames, adversarial games) to test defensive AI capabilities
• Designing and implementing RL environments for training defensive agents
• Pointing autonomous systems at real-world security challenges to characterize risks and develop mitigations

• Have strong software engineering skills, particularly in Python
• Have experience building and working with LLM-based agents or autonomous systems
• Are driven to find solutions to ambiguously scoped, high-stakes problems
• Design and run experiments quickly, iterating fast toward useful results
• Thrive in collaborative environments (we love pair programming!)
• Care deeply about AI safety and want your work to have real-world impact on how humanity navigates advanced AI
• Can own entire problems end-to-end, including both technical and non-technical components
• Are comfortable working on sensitive projects that require discretion and integrity

• Experience with reinforcement learning, self-play, or multi-agent systems
• Experience with robotics, hardware interfaces, or cyberphysical systems
• Track record of building demos or prototypes that communicate complex technical ideas
• Experience working with external stakeholders (policymakers, government, researchers)
• Familiarity with AI safety research and threat modeling for advanced AI systems