Senior Software Engineer, Systems
London, UKFull-TimeSeniorSoftware 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.
- 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 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.
Responsibilities
- Lead infrastructure projects from design through delivery, owning scope, execution, and outcomes
- Build and maintain systems that support AI clusters at massive scale (thousands to hundreds of thousands of machines)
- Partner with cloud providers and internal teams to solve compute, networking, and reliability challenges
- Tackle difficult technical problems in your domain and proactively fill gaps in tooling, documentation, and processes
- Contribute to operational practices including incident response, postmortems, and on-call rotations
You may be a good fit if you
- Have 6+ years of software engineering experience
- Have led technical projects end-to-end over multiple months, including scoping, breaking down work, and driving delivery
- Have deep knowledge of distributed systems, reliability, and cloud platforms (Kubernetes, IaC, AWS/GCP)
- Are strong in at least one systems language (Python, Rust, Go, Java)
- Solve hard problems independently and know when to pull others in
- Help teammates grow through knowledge sharing and thoughtful technical guidance
- Communicate clearly in design docs, presentations, and cross-functional discussions
Strong candidates may have
- 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
- Deadline to apply: None. Applications will be reviewed on a rolling basis.
- The annual compensation range for this role is listed below.
- For sales roles, the range provided is the role’s On Target Earnings ("OTE") range, meaning that the range includes both the sales commissions/sales bonuses target and annual base salary for the role.
How we're different
- 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.
