Staff+ Software Engineer, Safeguards ML Infrastructure

<div class="content-intro"><h2><strong>About Anthropic</strong></h2> <p>Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.</p></div><div> <h2>About the role</h2> </div> <div> <p>The Safeguards ML Infra team designs, builds, and operates the production infrastructure that powers Claude's safety systems. We own both the critical backend services that ensure safety on the token generation path, as well as the infrastructure that configures these systems during model provisioning for every platform Claude runs on -- 1P, Bedrock, Vertex, and beyond. We define and maintain SLOs, build the observability systems that surface problems early, and lead incident response when issues arise.</p> <p>We're growing the team and looking for Software Engineers with deep experience owning production infrastructure at scale. The ideal candidate has built and operated large-scale distributed systems under real production pressure and built platforms, tooling, and infrastructure that other engineers depend on. Familiarity with ML research or transformer architectures is not required -- you will learn that on the job. What we prioritize is distributed backend systems expertise and a track record of ownership over the production environment.</p> </div> <h2>Responsibilities:</h2> <ul> <li>Design, build, and deploy backend services that are critical safety pieces on the token sampling and generation path.</li> <li>Own and operate the production serving infrastructure for those services across multiple deployment platforms (1P, AWS Bedrock, GCP Vertex).</li> <li>Define and maintain SLOs, build observability and alerting systems, and lead incident response for infrastructure on the critical path of every Claude request</li> <li>