Infrastructure Engineer, Developer Velocity

We Love AI Jobs; San Francisco (CA); Hybrid; USD 347,000 - 445,000; Full time

Job summary

We Love AI Jobs is seeking an experienced Software Engineer to join the OpenAI San Francisco velocity team in a hybrid role. You will improve local development, build systems, CI, deployment pipelines, and production signals to reduce delays and manual intervention.

The role requires hands-on expertise with Bazel, Buildkite, Kubernetes, Temporal, Python and TypeScript services, and a bias for shipping reliable systems that engineers trust.

Qualifications

• Experience with large-scale developer infrastructure and CI/CD systems.
• Ability to debug across local machines, devboxes, and monorepos.
• Proven track record of improving build performance and reliability.
• Strong collaboration and ownership of end-to-end improvements.

Responsibilities

• Reduce local development startup and iteration latency for ChatGPT engineers.
• Improve Bazel and build performance for local machines, devboxes, and CI, including cache effectiveness and observability.
• Improve CI reliability and merge throughput by reducing unrelated failures and flaky tests.
• Build agents that help PRs make forward progress: rebasing, conflict resolution, CI triage, safe reruns.
• Make deploy pipelines more self-healing and resilient to transient issues.
• Improve deploy observability to quickly identify blockers and owners.
• Establish lightweight metrics for before-and-after impact: latency, throughput, and failure rates.

Tools

Bazel

Buildkite

Kubernetes

Temporal

Python

TypeScript

GitHub workflows

CI/CD

Job description

We Love AI Jobs is seeking an experienced Software Engineer to join the OpenAI San Francisco velocity team in a hybrid role. You will improve local development, build systems, CI, deployment pipelines, and production signals to reduce delays and manual intervention.

The role requires hands-on expertise with Bazel, Buildkite, Kubernetes, Temporal, Python and TypeScript services, and a bias for shipping reliable systems that engineers trust.