Software Engineer, Privacy EngineeringActive$230K–$325K

The opportunity

The Privacy Engineering team builds the systems and technical foundations that govern how user data is understood, retained, accessed, and used across OpenAI. We partner with Product, Data, Infrastructure, Security, and Legal to translate policy and trust commitments into durable architecture and enforceable controls.

What you'll do

  • Set the technical strategy and architecture for user data governance across: data mapping, classification, lineage, retention, deletion, access, and permitted usage.

  • Design and build shared services, APIs, metadata systems, and: policy-enforcement mechanisms that make governance controls consistent, scalable, and auditable.

  • Establish reliable inventories of user data, system ownership, data flows,: and policy applicability across products, infrastructure, analytics, and research systems.

  • Partner with Product, Data, Infrastructure, Security, and Legal leaders to: define decision rights, translate requirements into controls, and drive adoption across teams.

  • Own governance systems in production through measurable controls,: observability, migrations, exception handling, incident response, and continuous improvement.

  • Have substantial experience designing and operating large-scale data: platforms, privacy infrastructure, or governance systems in complex production environments.

What they're looking for

  • Have led architecture and multi-team execution for one or more: data-governance domains, such as metadata and lineage, retention and deletion, access governance, or data-use controls.
  • Can translate ambiguous policy, legal, security, and product requirements: into clear system boundaries, technical standards, phased roadmaps, and measurable outcomes.
  • Influence senior stakeholders and engineering teams without relying on formal: authority, communicate tradeoffs clearly, and build durable cross-functional alignment.
  • Take end-to-end ownership of high-trust systems, including correctness,: scalability, auditability, operational resilience, and the developer and operator experience.