Research Engineer, Frontier Red Team (autonomy)

Anthropic Anthropic · AI Frontier · San Francisco, CA · AI Research & Engineering

Research Engineer focused on building and evaluating autonomous AI systems and defensive agents to counter adversarial AI, with a focus on cyberphysical risks and AI safety. This role involves creating model organisms, developing defensive agents, and translating findings into policy-relevant demonstrations.

What you'd actually do

  1. 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
  2. Create evals and training environments to understand and shape agent behavior in desirable ways
  3. Develop defensive agents that can detect, disrupt, or outcompete adversarial AI systems in realistic scenarios
  4. Interface Claude with hardware platforms (e.g. robotics, physical systems) to understand cyberphysical risks and defenses
  5. Translate technical findings into compelling demonstrations and artifacts that inform policymakers and the public

Skills

Required

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

Nice to have

  • 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

What the JD emphasized

  • self-improving, highly autonomous AI systems
  • cyberphysical capabilities
  • autonomous AI systems
  • defensive agents
  • AI safety
  • cyberphysical risks
  • AI safety research

Other signals

  • autonomous AI systems
  • defensive agents
  • AI safety
  • cyberphysical risks