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About the Role
Anthropic's Infrastructure organization builds and operates the distributed systems that train, serve, and secure our AI models. As a Staff Software Engineer on the Infrastructure team, you'll scope and lead complex, multi-month infrastructure projects, make architectural decisions, and work with research and product teams to build systems that keep pace as their needs change.
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
Requirements
- 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
Skills
- Python
- Rust
- Go
- Java
- Kubernetes
- Infrastructure-as-code
- AWS
- GCP
- Machine learning infrastructure
- GPUs
- TPUs
- Trainium
- NCCL
- Linux kernel tuning
- eBPF
- Security engineering
- Privacy engineering
Location
- San Francisco
Work Type
- Hybrid
Experience Level
- Staff
- 10+ years of software engineering experience (preferred)
- Prior experience as a technical lead or mentor for other engineers (preferred)
Education Level
- Bachelor’s degree or an equivalent combination of education, training, and/or experience
- A field relevant to the role as demonstrated through coursework, training, or professional experience
Salary/Compensations
- £325,000—£390,000 GBP
Benefits
- Optional equity donation matching
- Generous vacation
- Parental leave
- Flexible working hours
About the Company
- 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.
- We believe that the highest-impact AI research will be big science.
- At Anthropic we work as a single cohesive team on just a few large-scale research efforts.
- We value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles.
- We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science.
- We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time.
- Anthropic is a public benefit corporation headquartered in San Francisco.
Equal Opportunity
- We encourage you to apply even if you do not believe you meet every single qualification.
- Not all strong candidates will meet every single qualification as listed.
- Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work.
- We think AI systems like the ones we're building have enormous social and ethical implications.
- We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.