Senior Software Engineer, Infrastructure

About the Team The Statsig team within OpenAI owns the experimentation, rollout, dynamic configuration, and analytics infrastructure that sits on the launch path for OpenAI products. Our systems help teams ship safely, evaluate product and model changes in production, and make high-confidence decisions from real-world usage. Statsig began as an independent company built around experimentation, feature management, and product analytics at scale. After Statsig joined OpenAI, the team began the next chapter: bringing that platform expertise and infrastructure into OpenAI as the experimentation and rollout foundation for every product we ship. This is infrastructure with a very direct product consequence. Teams working on ChatGPT, Codex, model measurement, consumer experiences including ads, business subscriptions, developer products, and shared platform systems depend on Statsig to evaluate configurations, move traffic safely, ingest experiment data, serve analytics, and roll changes forward or back when production reality demands it. We are at a critical point in the platform journey. Adoption is accelerating quickly across OpenAI, and the systems that were already important are becoming load-bearing for how the company launches. The infrastructure needs to stay fast under sharply increasing evaluation volume, reliable when more services depend on it, observable enough to debug quickly, and efficient enough to support OpenAI-wide scale. Recent SDK and server-side infrastructure work has already produced measurable wins in latency, reliability, memory usage, and compute efficiency across important services. The next phase is to make those gains systematic: a platform that can absorb rapidly growing product velocity while preserving low latency, data quality, operational safety, and developer trust. Based out of OpenAI's Bellevue office, we are a close-knit team that values in-person collaboration, technical depth, operational ownership, and building infrastructure that lets other builders move faster without taking on hidden reliability risk. About the Role As a Senior Infrastructure Engineer on the Statsig team, you will build and scale the foundational systems behind OpenAI's experimentation and rollout platform. You will work on the distributed control plane, SDK and server evaluation paths, ingestion pipelines, analytics foundations, and operational tooling that make launches safe and measurable at OpenAI scale. This role is deeply technical and centered on performance, scalability, reliability, and correctness. You will design systems that serve low-latency configuration decisions, handle high-throughput event ingestion, preserve data availability for experimentation and analytics workflows, and keep critical launch infrastructure dependable as usage grows. The work matters because OpenAI's next phase depends on learning quickly without compromising safety or reliability. Every major product surface needs a trusted way to evaluate changes, progressively roll them out, understand impact, and recover cleanly. Statsig is one of the core infrastructure layers that makes that possible. In This Role, You Will - Design and operate low-latency configuration delivery systems powering feature flags, dynamic configs, and progressive rollouts across OpenAI product suites. - Scale SDK, server-side evaluation, and control-plane systems so high-volume services can depend on Statsig without adding user-visible latency or operational fragility. - Build high-throughput data ingestion and analytics infrastructure for experimentation, product analytics, feature performance monitoring, and model or product measurement workflows. - Improve performance, efficiency, reliability, and observability of core Statsig infrastructure as OpenAI products scale globally. - Optimize query performance, data freshness, and data availability for teams making launch decisions from experimentation and analytics workflows. - Strengthen operational excellence through better SLOs, alerting, debugging tools, incident response, capacity planning, and failure-mode design. - Partner with teams across ChatGPT, Codex, model measurement, consumer ads, business subscriptions, developer products, and infrastructure to turn recurring launch and measurement needs into durable platform capabilities. - Lead large technical initiatives and shape the architecture of experimentation and rollout infrastructure used across the company. You Might Thrive In This Role If You - Have experience building large-scale distributed systems with strict performance, availability, and correctness requirements. - Enjoy low-latency systems work, including real-time configuration delivery, SDK/runtime performance, caching, concurrency, and high-throughput service design. - Have built or operated large-scale data platforms, event pipelines, analytics systems, or query infrastructure where freshness and correctness matter. - Care deeply about reliability, observa

You Might Thrive In This Role If You have experience building large-scale distributed systems with strict performance, availability, and correctness requirements. You enjoy low-latency systems work, including real-time configuration delivery, SDK/runtime performance, caching, concurrency, and high-throughput service design. You have built or operated large-scale data platforms, event pipelines, analytics systems, or query infrastructure where freshness and correctness matter.

Design and operate low-latency configuration delivery systems powering feature flags, dynamic configs, and progressive rollouts across OpenAI product suites. Scale SDK, server-side evaluation, and control-plane systems so high-volume services can depend on Statsig without adding user-visible latency or operational fragility. Build high-throughput data ingestion and analytics infrastructure for experimentation, product analytics, feature performance monitoring, and model or product measurement workflows. Improve performance, efficiency, reliability, and observability of core Statsig infrastructure as OpenAI products scale globally. Optimize query performance, data freshness, and data availability for teams making launch decisions from experimentation and analytics workflows. Strengthen operational excellence through better SLOs, alerting, debugging tools, incident response, capacity planning, and failure-mode design. Partner with teams across ChatGPT, Codex, model measurement, consumer ads, business subscriptions, developer products, and infrastructure to turn recurring launch and measurement needs into durable platform capabilities. Lead large technical initiatives and shape the architecture of experimentation and rollout infrastructure used across the company.