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OpenAI

Software Engineer, Enterprise Verticals

San Francisco (Remote)$293k–$325kfulltimemidAdded yesterday

About this role

OpenAI seeks a full-stack product engineer to build enterprise-focused ChatGPT workflows. You'll own end-to-end projects from customer discovery through production rollout, collaborating across design, research, and platform teams to deliver reliable AI-powered solutions for high-value business processes.

What you'll do

  • Design and deploy role-specific workflows across ChatGPT Work surfaces, plugins, and connectors
  • Translate customer insights into actionable product decisions with measurable quality metrics
  • Develop and maintain robust evaluation frameworks, monitoring, and safe rollback mechanisms
  • Partner cross-functionally with Design, Research, GTM, Security, and platform engineering
  • Manage full product lifecycle from prototype through phased rollout and iterative improvement
  • Ensure compliance with enterprise security, permissions, privacy, and reliability standards

What they're looking for

  • Full-stack product engineering (frontend, backend, APIs)
  • Systems integration and data engineering
  • Product judgment and ambiguous problem-solving
  • Observability, testing, and evaluation design
  • Cross-functional communication and customer engagement
  • Enterprise security and compliance practices
  • AI/LLM product development
  • Rollout strategy and risk management
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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.

View all jobs at OpenAI

Likely interview questions

  • Walk us through a time you shipped a feature across ambiguous requirements—how did you validate success?
  • Describe your experience integrating multiple systems or APIs; how did you handle unexpected dependencies?
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