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YubHub-native raw fields carry `x-` prefix.","jobs":[{"@context":"https://schema.org","@type":"JobPosting","identifier":{"@type":"PropertyValue","name":"YubHub","value":"job_6e48ec86-b97"},"title":"Security Labs Engineer","description":"<p><strong>About the Role</strong></p>\n<p>Security at Anthropic is not a compliance exercise. It is a core part of how we stay safe as we build increasingly capable systems. Our Responsible Scaling Policy commits us to launching structured security R&amp;D projects: ambitious, time-boxed experiments designed to resolve high-uncertainty questions about our long-term security posture.</p>\n<p>Each project runs for roughly 6 months with defined exit criteria. Some will succeed and move toward production. Others will fail, and we&#39;ll treat that as useful signals. The questions these projects are designed to answer include:</p>\n<ul>\n<li>Can our core research workflows survive extreme isolation?</li>\n<li>Can we get cryptographic guarantees where we currently rely on trust?</li>\n<li>Can AI become our most effective security control?</li>\n</ul>\n<p>As a Security Labs Engineer, you own one or more projects end-to-end: scoping the experiment, building the infrastructure, coordinating across teams, running the pilot, documenting results, and where the experiment succeeds, helping scale it into production. This is 0-to-1 and 1-to-10 work.</p>\n<p><strong>Current Project Areas</strong></p>\n<p>The portfolio evolves based on what we learn. Current areas include:</p>\n<ul>\n<li>Designing and operating a mock high-assurance research environment: simulating what our infrastructure would look like under extreme isolation and physical security controls, with real measurement of productivity impact</li>\n<li>Exploring cryptographic verification of model integrity using techniques like zero-knowledge proofs to provide mathematical guarantees about what is running in production</li>\n<li>Assessing the feasibility of confidential computing across the full model lifecycle (note: this is an open question, not a committed roadmap item)</li>\n<li>Piloting AI-assisted security tooling including vulnerability discovery, automated patching, anomaly detection, and adaptive behavioral monitoring</li>\n<li>Prototyping API-only access regimes where even internal research workflows never touch raw model weights</li>\n</ul>\n<p>Part of your job is helping shape what comes next based on gaps uncovered in the current round.</p>\n<p><strong>Responsibilities</strong></p>\n<ul>\n<li>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</li>\n<li>Build novel security infrastructure under real time pressure: isolated clusters, hardened access controls, cryptographic verification layers, with a bias toward learning fast</li>\n<li>Where experiments succeed, drive them toward production scale. An experiment that works on one cluster but not a hundred is not a finished result.</li>\n<li>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</li>\n<li>Evaluate and integrate emerging security technologies through coordination with external vendors and research groups</li>\n<li>Turn experimental results into clear, decision-ready writeups that inform Anthropic&#39;s long-term security architecture and RSP commitments</li>\n<li>Maintain a pain-point registry and feasibility assessment for each project, feeding directly into the design of production high-assurance environments</li>\n<li>Help scope and prioritize the next wave of Labs projects based on what the current round uncovers</li>\n</ul>\n<p><strong>Requirements</strong></p>\n<ul>\n<li>7+ years of software or security engineering experience, with a solid foundation in production systems</li>\n<li>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</li>\n<li>Strong programming skills in Python and at least one systems language (Go, Rust, or C/C++)</li>\n<li>Hands-on experience with cloud infrastructure (AWS, GCP, or Azure), Kubernetes, and networking fundamentals sufficient to stand up and tear down isolated environments quickly</li>\n<li>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</li>\n<li>Clear written communication: you know how to turn six weeks of experimentation into a two-page memo someone can act on</li>\n<li>Comfort with ambiguity and iteration, having run experiments that failed, extracted the lesson, and moved forward</li>\n<li>Genuine curiosity about what it would actually take to defend against a nation-state-level adversary</li>\n<li>Passion for AI safety and a real understanding of the role security plays in making frontier AI development go well</li>\n<li>Bachelor&#39;s degree in Computer Science, a related field, or equivalent industry experience required.</li>\n</ul>\n<p><strong>Nice to Have</strong></p>\n<ul>\n<li>Prior experience in offensive security, red teaming, or security research, having thought adversarially about systems and knowing which threats actually matter</li>\n<li>Familiarity with airgapped or high-side environments (classified networks, ICS/SCADA, financial trading infrastructure, or similar) and the operational realities of working inside them</li>\n<li>Knowledge of applied cryptography: zero-knowledge proofs, attestation protocols, secure enclaves, TPMs, or confidential computing primitives</li>\n<li>Experience with ML infrastructure (training pipelines, inference serving, model packaging) sufficient for grounded conversations with researchers about what their workflows actually need</li>\n<li>Background building or operating security systems in environments that demand rapid iteration rather than rigid change control</li>\n<li>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</li>\n</ul>\n<p style=\"margin-top:24px;font-size:13px;color:#666;\">XML job scraping automation by <a href=\"https://yubhub.co\">YubHub</a></p>","url":"https://yubhub.co/jobs/job_6e48ec86-b97","directApply":true,"hiringOrganization":{"@type":"Organization","name":"Anthropic","sameAs":"https://www.anthropic.com/","logo":"https://logos.yubhub.co/anthropic.com.png"},"x-apply-url":"https://job-boards.greenhouse.io/anthropic/jobs/5153564008","x-work-arrangement":"hybrid","x-experience-level":"senior","x-job-type":"full-time","x-salary-range":"$405,000-$485,000 USD","x-skills-required":["Python","Go","Rust","C/C++","Cloud infrastructure","Kubernetes","Networking 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