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 is seeking talented and experienced Software Engineers to join our Builds team within the Developer Platform organization. The Builds team owns the build infrastructure that every engineer and researcher at Anthropic depends on—from hermetic build environments and container image pipelines to remote build execution, build caching, and dependency management across our monorepo. By joining this team, you'll have a direct impact on the velocity and reliability of Anthropic's research and product development.
- As Anthropic scales its engineering organization, research ambitions, and the volume of code contributed by both humans and AI agents, build infrastructure is becoming a critical bottleneck and a critical lever. We're building next-generation systems—scalable remote build execution with content-addressable storage, fine-grained incremental builds, and hermetic reproducible environments—to ensure that build times shrink even as the codebase grows by orders of magnitude.
- Our monorepo spans Python, Rust, and Go, with builds targeting multiple accelerator platforms (TPUs, Trainium, GPUs) and complex SDK dependencies. This creates uniquely challenging problems in hermeticity, caching, cross-language interop, and dependency management that few organizations encounter. If you've built or operated large-scale, hermetic build infrastructure at a company with a large monorepo and are excited about designing systems that keep thousands of engineers productive, this is the role for you.
Responsibilities
- Design and build scalable, hermetic build infrastructure including remote build execution (RBE) and content-addressable storage (CAS) systems that support all source and image builds
- Own and evolve Nix-based build environments and package management, keeping nixpkgs and language runtimes current and compatible
- Drive fine-grained dependency management across the monorepo to enable incremental builds and eliminate unnecessary rebuilds
- Build and maintain language-specific build toolchains and accelerator SDK/runtime builds
- Reduce container image build times through architectural improvements to build pipelines, layer caching, and content-addressable storage
- Partner with CI, Languages, and Developer Acceleration teams to ensure build infrastructure integrates seamlessly with the broader developer platform
You May Be a Good Fit If You
- Have 6+ years of relevant industry experience building and operating large-scale build systems and infrastructure
- Have deep experience with hermetic, reproducible build systems (Bazel, Buck, Nix, or similar) in a large monorepo environment
- Understand build caching strategies, remote execution, and content-addressable storage deeply
- Have experience with containerized build environments and image build pipelines
- Have strong proficiency in at least one of Python, Rust, or Go
- Have excellent communication skills and enjoy supporting internal partners to improve their development experience
- Are excited about designing foundational systems and are comfortable working independently on ambiguous, high-impact technical challenges
Strong Candidates May Also Have
- Experience with Nix/NixOS and managing large Nix package sets at scale
- Experience with Rust build toolchains (cargo, maturin) and Python-Rust interop
- Experience building or operating remote build execution systems (Bazel Remote Execution API, BuildBarn, BuildBuddy, or similar)
- Experience managing accelerator SDK builds (CUDA, Neuron SDK, JAX/XLA)
- Experience with fine-grained dependency graph analysis and incremental build optimization at monorepo scale
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.
