About this role
About Anthropic
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.
About the role
Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. That includes data pipelines, some of the largest Kubernetes clusters in the world, and the databases, observability, and developer tooling that every other team at Anthropic depends on.
As a Staff Software Engineer on the Infrastructure team, you'll scope and lead complex, multi-month infrastructure projects, make the architectural decisions other engineers build on, and work with research and product teams to build systems that keep pace as their needs change.
Team placement happens after the interview process, based on your interests and experience alongside organizational needs. This helps us match you with the team where you'll have the most impact.
Key responsibilities
• Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system
• Make architectural decisions that shape the foundation other engineers and teams build on
• Drive alignment on technical direction across teams, working through ambiguous problem spaces
• Partner with research and product teams to understand their infrastructure and compute needs, and turn them into technical designs
• Own the reliability, scalability, and security of the systems you build as usage and complexity grow
• Set technical strategy and standards for your team's infrastructure
• Build and improve operational processes such as incident response, postmortems, and on-call rotations, so the team learns from every incident
• Mentor other engineers and help raise the technical bar for the team
Minimum qualifications
• Experience designing, building, and operating large-scale distributed systems or infrastructure in production
• A history of independently scoping and delivering complex, ambiguous, multi-month technical projects
• Experience making architectural decisions that other engineers and teams build on
• Strong software engineering fundamentals and proficiency in at least one programming language (for example, Python, Rust, Go, or Java)
• Experience with modern cloud infrastructure, including Kubernetes and infrastructure-as-code, on AWS and/or GCP
• Strong written and verbal communication skills, with experience driving alignment across teams or stakeholders
Preferred qualifications
• 10+ years of software engineering experience, not including internships
• Experience with machine learning infrastructure such as GPUs, TPUs, or Trainium, and associated networking like NCCL
• Low-level systems experience, such as Linux kernel t