Staff Software Engineer, Anthropic

• Deep expertise in distributed systems, reliability, and cloud platforms (e.g., Kubernetes, IaC, AWS/GCP/Azure)
• Strong proficiency in at least one systems language (e.g., Rust, Go, or Python), IaC proficiency with Terraform
• Hands-on experience with machine learning accelerators (GPUs, TPUs, or Trainium)
• Track record of leading complex, multi-quarter technical initiatives that span multiple teams or systems
• Ability to build alignment across senior stakeholders and communicate effectively at all levels
• Required field of study: A field relevant to the role as demonstrated through coursework, training, or professional experience
• Minimum years of experience: Years of experience required will correlate with the internal job level requirements for the position
• Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices
• Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this
• We encourage you to apply even if you do not believe you meet every single qualification

Desirable

• Anthropic's Infrastructure organization is foundational to our mission of developing AI systems that are reliable, interpretable, and steerable
• The systems we build determine how quickly we can train new models, how reliably we can run safety experiments, and how effectively we can scale Claude to millions of users — demonstrating that safe, reliable infrastructure and frontier capabilities can go hand in hand
• Node Infra owns the full lifecycle of accelerator capacity at Anthropic
• We ingest and provision compute from all major CSPs and our own datacenters, stand up and scale clusters from thousands to hundreds of thousands of hosts, and build the health, diagnostics and repair automation that keep every GPU, TPU and Trainium node in the fleet usable and ready to power Anthropic’s frontier AI research
• Own the technical strategy and roadmap for node lifecycle management - ingestion, bring-up, health checking, and automated repair
• Drive cross-team initiatives to build and scale AI clusters across multiple clouds and accelerator families
• Design and operate the systems that detect, isolate, and remediate unhealthy hardware automatically, driving up fleet MTBI and minimizing stranded capacity
• Define infrastructure architecture, ensuring the hardest problems get solved - whether by you directly or by working through others
• Work closely with cloud providers and internal research/inference/product teams to shape long-term compute, data, and infrastructure strategy
• Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)
• Support the growth of engineers around you through technical mentorship and coaching