Systems Integration Engineer, Build Systems | Consumer Devices

Excerpt from the original posting

About the Team 
The Systems Integration team is responsible for building the infrastructure, tooling, and validation systems that ensure our device software our device software is reliable, testable, and ready to ship. We design and maintain build systems, CI pipelines, automated test frameworks, and hardware-in-the-loop labs to enable rapid, safe product launches. Our work spans build systems, developer tools, systems integration, and cross-team collaboration to ensure developers can build reliably and ship with confidence.
About the Role 
We are looking for an engineer to help evolve OpenAI’s Consumer Products build and continuous integration systems for a fast-growing engineering organization. This role sits at the intersection of developer productivity, build systems, distributed infrastructure, software quality, and on-device software. You will work on the systems that determine how quickly and confident engineers can move: Bazel-bazed builds, Buildkite pipelines, test coverage, remote caching and execution, CI observability, and tooling that helps engineers understand and fix failures quickly.
Our mission is to enable OpenAI to ship software running on consumer devices rapidly with a high bar for correctness, reliability, and safety. The best version of this work is invisible when it succeeds: builds are fast, tests are trusted, CI failures are understandable, and engineers can focus on shipping products instead of fighting infrastructure.
This role is based in San Francisco, CA. We use a hybrid work model of four days in the office per week and offer relocation assistance to new employees.
In This Role, You Will 
- Own and evolve Bazel and yocto-based build and test workflows in a polyrepo environment

- Design and maintain Starlark rules, macros, toolchains, and integrations that make builds hermetic, reproducible, and easy for teams to adopt

- Improve CI performance and reliability across Buildkite pipelines, including queue time, build time, cache hit rates, retry behavior, and flake isolation.

- Build systems that reduce unnecessary CI work through affected-target detection, dependency graph analysis, test selection, caching, batching, and smarter scheduling

- Unify local and CI development workflows so engineers can reproduce CI behavior, debug build failures, and iterate quickly without learning every detail of the build stack

- Operate and optimize build infrastructure across Docker/OCI images, Kubernetes-based runners, cloud resources, a…

→ OpenAI · Ashby