[Pipeline] Staff+ Software Engineer, Systems

Anthropic•Seattle, WA

11h•Hybrid

About The Position

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. 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. The Systems engineering team owns compute uptime and resilience at massive scale, building the clusters, automation, and observability that make frontier AI research possible and safely deployable to customers. Team Matching: Team matching is determined after the interview process based on interview performance, interests, and business priorities. Please note we may also consider you for different Infrastructure teams.

Requirements

Have 10+ years of software engineering experience
Have led complex, multi-quarter technical initiatives that span multiple teams or systems
Can set technical direction for a team, not just execute within it
Have deep expertise in distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
Are strong in at least one systems language (Python, Rust, Go, Java)
Naturally uplevel the engineers around you and can redirect efforts when things are heading off track
Build alignment across senior stakeholders and communicate effectively at all levels
We require at least a Bachelor's degree in a related field or equivalent experience.

Nice To Haves

Security and privacy best practice expertise
Experience with machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
Low level systems experience, for example linux kernel tuning and eBPF
Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

Responsibilities

Own the technical strategy and roadmap for your area, translating team-level goals into concrete execution plans
Drive cross-team initiatives to build and scale AI clusters (thousands to hundreds of thousands of machines)
Define infrastructure architecture, ensuring the hardest problems get solved — whether by you directly or by working through others
Partner with cloud providers and internal stakeholders to shape long-term compute, data, and infrastructure strategy
Establish and evolve operational excellence practices (incident response, postmortem culture, on-call)