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Software Engineer, Monetization Infrastructure

Open AI

Salary not specified
Dec 10, 2025
San Francisco, CA, US
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OpenAI is looking to build foundational systems for its monetization and ads products to scale access to intelligence responsibly, strengthen user trust, unlock economic opportunity, and support long-term innovation.

Requirements

  • Have 10+ years of experience building and operating large-scale distributed systems
  • Have experience designing mission-critical systems with demanding reliability, performance, and correctness requirements
  • Think in systems—architecture, data flows, operational concerns, observability, and long-term maintainability
  • Are comfortable defining technical direction in ambiguous 0→1 environments
  • Bonus: Experience in ads systems, marketplaces, AI/ML infra, or other monetization-intensive domains

Responsibilities

  • Design and build the foundational backend and infrastructure powering OpenAI’s monetization and ads systems
  • Architect large-scale distributed systems that meet strict requirements for reliability, privacy, security, and performance
  • Develop APIs, infrastructure services, and internal platforms that support ads creation, delivery, measurement, and optimization
  • Drive 0→1 infra development through rapid prototyping, experimentation, and iterative improvements
  • Contribute to the long-term technical strategy and roadmap for the monetization infra stack
  • Ensure high engineering rigor through excellent testing, documentation, observability, and operational best practices
  • Build for safety, privacy, fairness, and policy alignment from first principles

Other

  • This role is exclusively based in our San Francisco HQ.
  • We offer relocation assistance to new employees.
  • Work closely with Product, Research, and Design to translate requirements into scalable technical solutions
  • Enjoy working cross-functionally to shape product requirements and system capabilities
  • Communicate clearly, reason holistically, and make decisions grounded in user needs and long-term system health