Security Labs Engineer

Anthropic Anthropic · AI Frontier · San Francisco, CA · Security

This role focuses on executing security R&D projects end-to-end, building novel security infrastructure, and driving successful experiments toward production scale. It involves working with research teams to test security controls, evaluating new security technologies, and documenting results to inform future security architecture. The role spans from initial project scoping to potential production deployment, with a focus on high-assurance environments and AI-assisted security tooling.

What you'd actually do

  1. Own the end-to-end execution of a Security Labs project: refine the hypothesis, design the experiment, build the prototype, run the pilot, and write up the results
  2. Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast
  3. Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.
  4. Work embedded with research teams (Pretraining, RL, Inference) to stress-test whether their core workflows can function under extreme security controls, and document precisely where they break
  5. Evaluate and integrate emerging security technologies through coordination with external vendors and research groups

Skills

Required

  • 7+ years of software or security engineering experience
  • solid foundation in production systems
  • pilots, prototypes, or applied research work
  • Strong programming skills in Python
  • at least one systems language (Go, Rust, or C/C++)
  • Hands-on experience with cloud infrastructure (AWS, GCP, or Azure)
  • Kubernetes
  • networking fundamentals sufficient to stand up and tear down isolated environments quickly
  • track record of cross-functional execution
  • Clear written communication
  • Comfort with ambiguity and iteration

Nice to have

  • Prior experience in offensive security, red teaming, or security research
  • Familiarity with airgapped or high-side environments
  • Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives
  • Experience with ML infrastructure (training pipelines, inference serving, model packaging)
  • Background building or operating security systems in environments that demand rapid iteration rather than rigid change control
  • Prior work at a startup, on an innovation team, or in an applied research group

What the JD emphasized

  • end-to-end execution of a Security Labs project
  • build the prototype
  • run the pilot
  • write up the results
  • Build novel security infrastructure
  • isolated clusters
  • hardened access controls
  • cryptographic verification layers
  • drive them toward production scale
  • Work embedded with research teams
  • stress-test
  • document precisely where they break
  • Evaluate and integrate emerging security technologies
  • coordination with external vendors and research groups
  • Turn experimental results into clear, decision-ready writeups
  • inform Anthropic's long-term security architecture
  • RSP commitments
  • Maintain a pain-point registry
  • feasibility assessment
  • design of production high-assurance environments
  • Help scope and prioritize the next wave of Labs projects
  • 7+ years of software or security engineering experience
  • solid foundation in production systems
  • pilots, prototypes, or applied research work
  • shipping a working answer to a hard question was the explicit goal
  • Strong programming skills in Python
  • at least one systems language (Go, Rust, or C/C++)
  • Hands-on experience with cloud infrastructure (AWS, GCP, or Azure)
  • Kubernetes
  • networking fundamentals sufficient to stand up and tear down isolated environments quickly
  • track record of cross-functional execution
  • walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan
  • Clear written communication
  • turn six weeks of experimentation into a two-page memo someone can act on
  • Comfort with ambiguity and iteration
  • run experiments that failed, extracted the lesson, and moved forward
  • Genuine curiosity about what it would actually take to defend against a nation-state-level adversary
  • Passion for AI safety
  • real understanding of the role security plays in making frontier AI development go well
  • Prior experience in offensive security, red teaming, or security research
  • thought adversarially about systems and knowing which threats actually matter
  • Familiarity with airgapped or high-side environments
  • operational realities of working inside them
  • Knowledge of applied cryptography
  • zero-knowledge proofs
  • attestation protocols
  • secure enclaves
  • TPMs
  • confidential computing primitives
  • Experience with ML infrastructure (training pipelines, inference serving, model packaging)
  • grounded conversations with researchers about what their workflows actually need
  • Background building or operating security systems in environments that demand rapid iteration rather than rigid change control
  • Prior work at a startup, on an innovation team, or in an applied research group
  • shipping a working v0 to answer a real question was explicitly the goal

Other signals

  • Security R&D projects
  • End-to-end execution of projects
  • Build novel security infrastructure
  • Drive experiments toward production scale
  • Work embedded with research teams
  • Evaluate and integrate emerging security technologies
  • Turn experimental results into clear, decision-ready writeups
  • Help scope and prioritize the next wave of Labs projects