Staff+ Software Engineer, Research Systems Engineering

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 - systems that every other team at Anthropic depends on.

As a Staff+ Software Engineer on Research Systems Engineering, you'll work directly with our Research teams to build the reliable, scalable, performant infrastructure our research depends on. This is a cross-functional systems team: you'll scope and lead complex, multi-month infrastructure projects and resolve the performance and scalability bottlenecks that limit how fast we can grow.

Key responsibilities

• Independently scope and lead complex, multi-month infrastructure projects, from an ambiguous starting point through to a production system
• Develop deep understanding and partnerships with researchers and Research teams in order to deliver for them.
• Mentor other engineers and help raise the technical bar for the team
• Drive alignment on technical direction across multiple teams, working through ambiguous problem spaces
• Take ownership of the reliability, scalability, and security of the systems you build as usage and complexity grow
• Have a leadership role across Infrastructure to build and improve operational processes, such as incident response, postmortems, and on-call rotations, that help the team learn from every incident

Minimum qualifications

• Experience designing, building, and operating large-scale distributed systems or infrastructure in production
• A track record of independently scoping and delivering complex, ambiguous, multi-month technical projects
• Prior experience as a technical lead or mentor for other engineers
• Experience making architectural decisions that other engineers and teams build on top of
• 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 multiple 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 infrastructure like NCCL
• Low-level systems experience, such as Linux kernel tuning or eBPF
• Background in security or privacy engineering best practices