Systems Integration Engineer, Build Systems | Consumer Devices

About this role

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, and remote cache/execution systems

- Instrument build and CI systems with metrics, logs, traces, dashboards, and analytics so we can measure speed, reliability, cost, and developer impact

- Partner directly with users to understand pain points, onboard projects, debug hard build issues, and remove systemic bottlenecks

- Use modern AI tools to pioneer novel CI failure analysis, flaky test debugging, PR triage, automated remediation, and developer-facing information

- Own the reliability of the systems you build, including participating in an on-call rotation for critical developer and factory infrastructure

Technologies Commonly Used In This Environment Include

- Bazel and Starlark for build and test workflows

- Buildkite for CI orchestration

- Docker and OCI images for build and runtime packaging

- Kubernetes for CI runners and infrastructure orchestration

- Python, Go, TypeScript, Rust, C++, and other languages in a large monorepo

- Terraform for infrastructure as code

- Remote caching, remote execution, artifact storage, and build telemetry systems

You May Be A Strong Fit If You

- Have 5+ years of engineering experience, including significant experience building infrastructure and tooling for developers

- Have hands-on experience with Bazel, Buck, Gradle, or similar build systems, and understand the trade offs of hermetic builds, dependency graphs, caching, sandboxing, and remote execution

- Have built CI systems at scale, especially in environments where build time, queue time, test flakiness, and developer trust materially affect engineering velocity

- Are comfortable with owning production software and working in environments with strong SLA requirements

- Can debug distributed build and CI failures across source control, dependency management, containers, runners, remote caches, test frameworks, and service infrastructure.

- Care deeply about developer experience and have empty for the small sources of friction that slow teams down or create operational toil

- Are excited to apply AI to developer infrastructure in ways that increase team velocity without weakening quality, reliability, or safety

- Have operated in a polyrepo environment with source code from multiple parties

About OpenAI

OpenAI is an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity. 

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.

For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement https://cdn.openai.com/policies/eeo-policy-statement.pdf.

Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordina

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