Seattle, United States OpenAI Engineering Manager, Core Experimentation

Experimentation Jobs; Seattle (WA); On-site; USD 180,000 - 240,000; Full time

Job summary

OpenAI in Seattle seeks an Engineering Manager to lead the Core Experimentation team, shaping the platform that powers experimentation, feature flags, dynamic configuration, and rollout safety across products.

You will partner with product, research, data, and infrastructure leaders to translate recurring needs into durable capabilities that drive faster, safer product decisions. This role blends hands-on leadership with strategic planning to scale a high-performing engineering organization.

Qualifications

• 5+ years in engineering leadership or management of 2+ teams.
• Experience building or scaling experimentation/feature-flag platforms is a plus.

Responsibilities

• Lead and grow a high-performing core experimentation engineering team.
• Define multi-year product engineering strategy for experimentation and rollout safety.
• Partner with product, research, data, and infrastructure teams to deliver platform capabilities.

Skills

People leadership

Technical vision

Job description

Why Here?
OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. The Statsig team within OpenAI builds the experimentation, feature rollout, dynamic configuration, and analytics systems that help OpenAI ship products with speed, safety, and evidence. This work sits on the critical path for how product, engineering, research, and go-to-market teams learn from real-world usage and make high-confidence decisions. The team integrates deep product expertise into the platform used across ChatGPT, Codex, and other core initiatives.

What Will You Do?
As an Engineering Manager, Core Experimentation at OpenAI, you will build, lead, and scale a high-performing product engineering organization including managers and senior technical leaders. You will define the multi-year product engineering strategy for experimentation, feature flags, dynamic configuration, rollout safety, and analytics. Additionally, you will partner with leaders across product, research, data, and infrastructure teams to translate recurring needs into durable platform capabilities that drive company-wide adoption.