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OpenAI

Software Engineer, API Multimodal

San Francisco$293k–$385kfulltimemidAdded today

About this role

Join OpenAI's API Multimodal team to design and operate backend services and distributed systems powering image, audio, and real-time APIs. You'll partner with research and inference teams to bring frontier multimodal capabilities to developers while owning projects from design through production at scale.

What you'll do

  • Design and ship developer-facing APIs and backend services for frontier multimodal models
  • Build low-latency streaming and request handling systems that reliably serve complex multimodal interactions
  • Collaborate with Research teams to integrate new model capabilities into production and gather developer feedback
  • Own availability, latency, scalability, and cost efficiency of deployed services
  • Lead technically complex projects from ambiguous requirements through launch and iteration
  • Raise engineering standards and drive architectural improvements across the team

What they're looking for

  • Backend engineering (Python, Go, Rust, or TypeScript)
  • Distributed systems design and architecture
  • Production API and backend service development
  • Low-latency streaming and real-time systems
  • Observability, monitoring, and operational excellence
  • Developer empathy and API design
  • Cross-team collaboration and communication
  • Experience with audio, image, or multimodal systems (preferred)
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OpenAI

OpenAI builds AI infrastructure and products, including large-scale data center campuses for AI computing and generative AI applications for enterprise customers. The company is hiring civil engineers, project engineers, electrical design engineers, data center R&D engineers, and AI deployment engineers to expand its infrastructure capabilities and help customers deploy AI solutions.

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Likely interview questions

  • Describe a complex backend system you designed from scratch—how did you approach latency, scalability, and cost tradeoffs?
  • How would you approach integrating a new, experimental model capability into a production API while maintaining reliability?
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