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 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.
- 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
- 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
- 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 tuning or eBPF
- Background in security or privacy engineering best practices
- Prior experience as a technical lead or mentor for other engineers
Minimum education: Bachelor’s degree or an equivalent combination of education, training, and/or experience
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. 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.
Your safety matters to us. To protect yourself from potential scams, remember that Anthropic recruiters only contact you from @anthropic.com email addresses. In some cases, we may partner with vetted recruiting agencies who will identify themselves as working on behalf of Anthropic. Be cautious of emails from other domains. Legitimate Anthropic recruiters will never ask for money, fees, or banking information before your first day. If you're ever unsure about a communication, don't click any links—visit anthropic.com/careers directly for confirmed position openings.
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. And 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. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues. Guidance on Candidates' AI Usage: Learn about our policy for using AI in our application process.
