The Safeguards ML Infra team designs, builds, and operates the production infrastructure that powers Claude’s safety systems
We own the critical backend services that ensure safety on the token generation path, and we own the operational work of getting those systems safely into production: standing up safeguards for every new model launch, and deploying new safety classifiers as they ship
Every frontier model release runs through this team – we configure, verify, and roll out safeguards across every platform Claude runs on (1P, AWS Bedrock, GCP Vertex, etc), and we lead incident response when issues arise. This role sits at the center of that operational work
You’ll ensure safeguards are properly configured and deployed for model launches and own the off-cycle deployment of new safety classifiers — canarying changes, verifying that the right safeguards are provably live on the right models, and holding rollback authority when something looks wrong
Every launch should also shrink the checklist, and the manual verifications should evolve into a system that runs itself
You’ll turn launch runbooks into tooling, hand-built checks into continuous validation, and one-off deploys into a repeatable pipeline
What we prioritize is production judgment: a track record of shipping changes to critical systems safely, and of automating yourself out of the work you did last quarter
Launch captain model releases: stand up, configure, and verify safeguards for every new model, and serve as the safeguards point of contact in the launch room during release windows
Own the off-cycle deployment of new safety classifiers as they ship from research — canarying rollouts, running post-deploy validations, and investigating discrepancies when something looks wrong
Verify that the right safeguards are provably live on the right models across every deployment platform (1P, AWS Bedrock, GCP Vertex, etc.), and detect and eliminate configuration drift between them
Automate yourself out of last quarter’s work: turn launch runbooks into tooling, hand-built checks into continuous validation, and one-off deploys into a repeatable pipeline
Plan to use Claude aggressively to do this! And be a trailblazer that paves the path for safe agentic operations of safety-critical systems
Build and maintain a safeguards registry with full provenance — what is running in production, on which model, on which platform, and when and by whom it was deployed
Participate in on-call and operational-duty rotations covering service incidents, model provisioning, and time-sensitive research and safety launches
Benefits
Comprehensive health, dental, and vision insurance for you and your dependents
Inclusive fertility benefits via Carrot Fertility
22 weeks of paid parental leave
Flexible paid time off and absence policies
Mental health support for you and your dependents
Competitive salary and equity packages
Optional equity donation matching at a 1:1 ratio, up to 25% of your equity grant
Retirement plans with competitive matching
Life and income protection plans
$500/month flexible wellness and time saver stipend
Commuter benefits
Annual education stipend
Home office stipends
Relocation support for those moving for Anthropic
Daily meals and snacks in the office- We’re looking for engineers with deep experience in production change management at scale — people who have owned deploy pipelines, config management systems, rollout safety, or launch readiness for systems under real production pressure
Familiarity with ML research or transformer architectures is not required — you will learn that on the job
Have a desire to close the gap where nobody has yet raised their hand, even if it requires manually hand-holding processes until automation and tooling can be built
Are proficient in Python; experience with Rust is a plus but not required
Have owned production change management at scale — deploy pipelines, config management systems, canary analysis — and have strong opinions about what “verified” means
Have hands-on experience deploying and operating on cloud platforms (AWS, GCP) at scale
Have run high-stakes releases: served as a launch captain, incident commander, or release owner for systems where a bad deploy has real consequences, and are energized rather than drained by being in the critical path
Have meaningful on-call experience for production systems, including incident response and postmortem-driven improvements — and a track record of turning (and fixing!) postmortem action items into process and tooling changes
8+ years of industry software engineering or site reliability engineering experience
A demonstrated history of reducing operational toil through automation, including transitioning teams from manual deployment processes to self-serve pipelines
Experience running launch or production-readiness review processes across multiple teams
Familiarity with LLM inference systems and the operational characteristics of transformer-based models
Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
We encourage you to apply even if you do not believe you meet every single qualification. We urge you not to exclude yourself prematurely and to submit an application if you’re interested in this work
