Software Engineer, IP Infrastructure

OpenAI•San Francisco, CA
•$266,000 - $405,000•Hybrid

About The Position

The IP Infrastructure team builds and operates systems that enable OpenAI to share research and engineering technology securely and reliably with strategic partners. Its work includes continuously running pipelines for model weights, configurations, code, and container images, in collaboration with research, security, developer infrastructure, and partner engineering teams. The Software Engineer will build and improve backend services for these workflows, primarily using Python. The role takes projects from design through production and improves system reliability and operability as partner integrations evolve. It involves translating sharing requirements into clear, testable business logic, debugging across system boundaries, and working with teams that build and use the underlying infrastructure. The position is based in San Francisco, California, with a hybrid work model requiring three days in the office per week.

Requirements

  • Strong Python skills and experience building, testing, and debugging backend software.
  • Experience taking a service, pipeline, or automation project from implementation into production and helping keep it reliable.
  • Ability to investigate how systems fit together and trace problems across services and dependencies.
  • Ability to turn ambiguous requirements into practical software while exercising sound judgment around sensitive information.
  • Clear communication with technical and nontechnical collaborators and willingness to work with partner engineering teams.
  • Ability to learn unfamiliar systems quickly and take responsibility for following problems through to resolution.

Nice To Haves

  • Experience with cloud services, object storage, containers, or CI/CD.
  • Familiarity with tools such as Docker, Bazel, and Buildkite; prior expertise in every tool or a particular cloud provider is not required.

Responsibilities

  • Build and maintain automated pipelines that transfer model weights, configurations, code, and container images between OpenAI and partner environments.
  • Implement validation and business logic that determines how artifacts are prepared and shared.
  • Improve production reliability through testing, monitoring, useful diagnostics, and robust failure handling.
  • Integrate services with source control, object storage, and build and container tooling, in collaboration with shared infrastructure owners.
  • Work with researchers, security teams, and external engineers to understand requirements and resolve integration problems.
  • Improve existing workflows and use AI tools where they can make the systems more effective.
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