Used Tools & Technologies
Not specified
Required Skills & Competences
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Go @ 7
Python @ 7
A/B Testing @ 4
CI/CD @ 4
Communication @ 4
Rust @ 7
API @ 4
Experimentation @ 4
AI @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. The Infrastructure organization builds systems that 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. 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 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
- Design and build scalable, reliable distributed infrastructure and shared libraries that support high-volume experimentation and config workloads across engineering teams
- Own and evolve 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
Requirements
- Deep experience with configuration management, feature flagging, and/or experimentation platforms in a large-scale environment
- Strong proficiency in Python, Rust, and/or Go
- Experience with container orchestration and infrastructure at scale
- 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
- Excellent communication skills and experience supporting internal partners to improve their development experience
- Ability to design foundational systems and work independently on ambiguous, high-impact technical challenges
Strong candidates may have
- 15+ years of experience in a Software Engineer role building and operating large-scale developer infrastructure
- 3+ years 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)
Logistics
- Location: San Francisco, CA or Seattle, WA
- Location-based hybrid policy: currently expect all staff to be in one of our offices at least 25% of the time (some roles may require more time in office)
- Minimum education: Bachelor’s degree or equivalent combination of education, training, and/or experience
- Visa sponsorship: The company states they do sponsor visas and retain an immigration lawyer to help where possible
Compensation
- Annual Salary: $405,000 - $485,000 USD
Benefits
- Competitive compensation and benefits
- Optional equity donation matching
- Generous vacation and parental leave
- Flexible working hours
- Office space for collaboration
How we're different
Anthropic works as a single cohesive team on a few large-scale research efforts. The company values impact, collaboration, frequent research discussions, and strong communication. Recent research directions include GPT-3, circuit-based interpretability, multimodal neurons, scaling laws, and learning from human preferences.
Application notes
- Deadline: Applications reviewed on a rolling basis
- The company encourages applicants who may not meet every qualification to apply
- Guidance on candidate AI usage is provided on the company careers site