[Pipeline] Staff+ Software Engineer, Experimentation

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.

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.
• Obsessed with developer productivity and reducing friction in how teams configure, test, and ship changes.
• Experience with container orchestration and infrastructure at scale.
• Excellent communication skills and enjoy supporting internal partners to improve their development experience.
• Excited about designing foundational systems and comfortable working independently on ambiguous, high-impact technical challenges.
• Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role.

Nice-to-Haves

• 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.