Extreme Security Jobs (NOW HIRING)

Job Summary:
Anthropic is on a mission to create reliable, interpretable, and steerable AI systems. As a Security Labs Engineer, you will own projects that focus on enhancing security through innovative experiments and infrastructure, working closely with research teams to ensure robust security measures are in place.
Responsibilities:
• 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
• Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast
• Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.
• 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
• Evaluate and integrate emerging security technologies through coordination with external vendors and research groups
• Turn experimental results into clear, decision-ready writeups that inform Anthropic's long-term security architecture and RSP commitments
• Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments
• Help scope and prioritize the next wave of Labs projects based on what the current round uncovers
Qualifications:
Required:
• 7+ years of software or security engineering experience, with a solid foundation in production systems
• Some of that time spent on pilots, prototypes, or applied research work where shipping a working answer to a hard question was the explicit goal
• Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)
• Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly
• A track record of cross-functional execution: you can walk into a room with ML researchers, infrastructure engineers, and vendors and leave with a shared plan
• Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on
• Comfort with ambiguity and iteration, having 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 and a real understanding of the role security plays in making frontier AI development go well
• Bachelor's degree in Computer Science, a related field, or equivalent industry experience required.
Preferred:
• Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter
• Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them
• 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) sufficient for 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 where shipping a working v0 to answer a real question was explicitly the goal
Company:
Anthropic is an artificial intelligence company that develops large language models and AI systems for business and research use. Founded in 2021, the company is headquartered in San Francisco, USA, with a team of 501-1000 employees. The company is currently Late Stage.