OpenAI

AI Deployment Engineer, Digital Natives

San Francisco (Remote)$197k–$278kfulltimemidAdded today

About this role

OpenAI seeks an AI Deployment Engineer to guide enterprise customers in building and scaling production Generative AI applications. You'll act as a technical thought partner, designing custom solutions using OpenAI APIs and driving adoption across use cases like customer service, content generation, and personalization.

What you'll do

Partner with enterprise customers to develop AI strategic roadmaps and identify high-value use cases
Design enterprise architectures using OpenAI APIs to maximize customer business impact
Prototype and validate solutions with customers, guiding them from concept to production deployment
Manage stakeholder relationships and ensure successful scaling of customer applications
Contribute to open-source resources and codify best practices for internal and external teams
Synthesize customer feedback and deliver actionable insights to Product, Engineering, and Research teams

What they're looking for

Python and JavaScript proficiency
Technical consulting or equivalent experience (5+ years)
OpenAI API platform expertise and prototyping
Complex project and program management with multiple stakeholders
Enterprise architecture and systems design
Customer-facing communication and relationship building
Problem-solving and self-directed learning
Ability to prioritize and manage multiple concurrent projects

Benefits

Hybrid work model (3 days in office per week)
Based in San Francisco or Seattle
Relocation assistance available
Work with frontier AI technology and cutting-edge models
Opportunity to influence product direction through customer feedback
Exposure to diverse enterprise use cases and industries

Likely interview questions

Walk us through a complex AI or technical project you led end-to-end—what was your role in navigating multiple stakeholders to success?
Describe your experience building prototypes or applications on top of LLM APIs. What were the biggest challenges and how did you solve them?

How would you approach identifying and validating high-impact AI use cases for an enterprise customer with little LLM experience?
Tell us about a time you received critical feedback from customers and how you channeled it back to a product or engineering team to drive change.
What strategies would you use to balance supporting multiple sophisticated customers simultaneously while maintaining high-quality technical guidance?
How do you stay current with frontier AI capabilities, and how would you communicate emerging opportunities to customers?
Describe a situation where you had to operate with ambiguity and limited information—how did you navigate it?

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