Anthropic-posted 3 months ago
$320,000 - $485,000/Yr
San Francisco, CA

Join Anthropic's Languages Team as a foundational member shaping how Python, Rust, and Go are used across one of the world's fastest-growing AI companies. As we scale our engineering and research teams, we are currently seeking three team members (one each for Python, Go and Rust), who are experts in the respective languages, to help define and build the development ecosystems that power the future of AI development. You'll be responsible for the full lifecycle of how Python, Rust, and Go are used by engineers and researchers across Anthropic - from research experiments to production systems serving millions. This includes building foundational language infrastructure, defining best practices, creating tooling, and ensuring exceptional developer productivity while supporting both cutting-edge AI research and massive-scale deployment. Working at the intersection of language ecosystems and AI development, you'll tackle uniquely complex problems where your architectural decisions directly impact how thousands of engineers develop AI systems safely and efficiently. The infrastructure you build must support diverse workloads - from experimental research code to battle-tested production systems - all while maintaining the highest standards of safety, performance, and developer experience. This is an opportunity to establish the standards and foundations for how modern programming languages enable AI development at unprecedented scale, working alongside some of the brightest minds in AI research and engineering.

  • Design and build foundational language infrastructure for Python, Rust, and/or Go that supports both AI research workflows and production-scale systems
  • Define and implement language ecosystem standards, best practices, tooling, libraries, and frameworks that ensure safety, performance, and exceptional developer productivity across diverse AI workloads
  • Establish language-specific CI/CD pipeline integration, testing frameworks, and deployment strategies optimized for AI development cycles
  • Partner extensively with infrastructure teams to ensure seamless integration between language-specific tools and broader platform services, such as debugging Kubernetes issues, optimizing node instance types for performance, and collaborating on cross-cutting infrastructure challenges
  • Collaborate closely with research and engineering teams to understand emerging requirements and translate them into robust, scalable language infrastructure, including cross-language interoperability solutions
  • Drive technical strategy for language adoption, migration paths, large-scale cross-cutting changes, and ecosystem evolution as Anthropic scales, while mentoring engineers and researchers on language best practices
  • Lead incident response and troubleshooting for language-related issues across research and production environments
  • Have 5+ years of production software engineering experience with deep expertise in at least one of Python, Rust, or Go
  • Have strong experience in developer tooling, build systems (including Nix), dependency management, and worked extensively with monorepos
  • Are comfortable working across the stack, including debugging infrastructure issues like Kubernetes problems or optimizing system performance
  • Have strong communication and collaboration skills to work effectively with diverse teams including researchers, engineers, and infrastructure specialists
  • Are excited about defining foundational systems and processes and are comfortable working independently on ambiguous, high-impact technical challenges
  • Built core language infrastructure like compilers, interpreters, package ecosystems, or maintained widely-used open-source developer tools with significant adoption
  • Expertise in performance optimization across language runtimes or cross-language interop technologies
  • Experience with AI/ML research-to-production workflows, understanding the unique challenges of supporting both experimental research code and production model training/serving pipelines
  • Competitive compensation and benefits
  • Optional equity donation matching
  • Generous vacation and parental leave
  • Flexible working hours
  • Lovely office space in which to collaborate with colleagues
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