[Pipeline] Staff+ Software Engineer, Experimentation

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.

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:

• 15+ years (not including internships or co-ops) of experience in a Software Engineer role, building and operating large-scale developer infrastructure
• 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

Pay

The annual compensation range for this role is listed below.

• Annual Salary: $405,000 - $485,000 USD

Logistics

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

We currently 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.

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.

Our research

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.

Guidance on Candidates' AI Usage

Learn about our policy for using AI in our application process.

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