Staff+ Software Engineer, Experimentation

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'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.

Developer Productivity owns the end-to-end experience of how engineers and researchers at Anthropic develop, build, test, and ship code at scale. This role focuses on the configuration and experimentation systems that let teams safely roll out changes, run controlled experiments, and make data-driven decisions across our products and infrastructure — from feature flagging and dynamic configuration to A/B testing platforms that support both research and production workloads

Responsibilities

Own the technical strategy and roadmap for config and experimentation infrastructure, translating team-level goals into concrete execution plans and partnering with teams focused on deployment, testing, and more Maintain and enhance the architecture for feature flagging, dynamic configuration, and experimentation systems, ensuring the hardest problems get solved — whether by you directly or by working through others Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume experimentation and config workloads across all engineering teams Own and evolve the platforms and tooling that let engineers and researchers safely ship config changes, run experiments, and measure impact Define standards, tooling, and frameworks for experimentation and configuration management that drive developer productivity across research and production workloads You may be a good fit if you: Have deep experience with configuration management, feature flagging, and/or experimentation platforms in a large-scale environment Have strong proficiency in Python, Rust and/or Go Are obsessed with developer productivity and reducing friction in how teams configure, test, and ship changes Have experience with container orchestration and infrastructure at scale 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 have: Have 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure Have 3+ years (not including internships or co-ops) of experience leading large scale, complex projects or teams as an engineer or tech lead Experience with config or experimentation platforms such as Statsig, GrowthBook, LaunchDarkly, Optimizely, Unleash, or similar (including building such systems in-house) Experience designing experimentation frameworks — randomization, assignment, metrics pipelines, and statistical analysis for A/B testing at scale Experience with dynamic configuration systems and safe rollout mechanisms (gradual rollouts, kill switches, targeting rules) Experience building CLI tools, developer-facing services, and APIs/automation workflows that integrate config and experimentation into existing CI/CD pipelines Deadline to apply: None.