Partner AI Deployment Engineer - Aws

OpenAI OpenAI · AI Frontier · London, United Kingdom · Go To Market

This role focuses on enabling the deployment of Generative AI applications for developers and enterprises by acting as a senior technical counterpart to AWS field leadership. The engineer will shape strategy, define engagement models, and build repeatable systems to scale adoption of OpenAI-powered solutions, guiding customers from ideation to production and enabling partners to independently drive deployments. The role involves designing AI architectures, building prototypes, establishing best practices for production-ready GenAI systems, and enabling the AWS ecosystem through scalable technical motions.

What you'd actually do

  1. Serve as the senior technical counterpart to AWS field leadership, building trust and credibility across regions and teams.
  2. Influence joint account strategy and technical direction for high-priority opportunities.
  3. Shape how OpenAI engages with AWS by defining engagement models, prioritization frameworks, and best practices.
  4. Proactively identify and drive net-new opportunities and high-impact use cases across the AWS ecosystem.
  5. Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements.

Skills

Required

  • 8+ years of technical consulting experience
  • managing C-level technical and business relationships with complex global organizations
  • technical leader and systems thinker
  • hands-on building
  • strategic influence and scale
  • owning ambiguous, high-visibility problem spaces

Nice to have

  • deep technical expertise
  • strong judgment
  • ecosystem leadership
  • balance hands-on building with strategic influence and scale
  • know when to go deep technically vs. enable others to execute
  • build trust quickly with engineers, architects, and executives alike
  • default to creating repeatable patterns, not one-off solutions
  • take a long-term, ecosystem-oriented view of impact
  • motivated by driving customer and partner success at scale

What the JD emphasized

  • primary technical counterpart to AWS field leadership
  • shape strategy
  • define engagement models
  • build repeatable systems that scale
  • guiding complex enterprise customers from ideation to production
  • enabling AWS and partners to independently drive deployments
  • ecosystem leadership
  • complex enterprise engagements
  • production deployment
  • partner-led delivery
  • Scale impact by working through GSIs, RSIs, and ISVs
  • ecosystem-oriented view of impact
  • driving customer and partner success at scale

Other signals

  • driving joint customer success
  • enabling AWS and partner ecosystems to scale adoption
  • shaping strategy
  • defining engagement models
  • building repeatable systems that scale
  • guiding complex enterprise customers from ideation to production
  • enabling AWS and partners to independently drive deployments
  • design and communicate end-to-end AI architectures
  • build and guide development of prototypes, POCs, and reference implementations
  • establish best practices for scalable, secure, and production-ready GenAI systems
  • ensure solutions are designed for repeatability, extensibility, and partner-led delivery
  • enable AWS and partners through scalable technical motions
  • develop reusable solution patterns and assets
  • mentor and uplift partner technical teams
  • scale impact by working through GSIs, RSIs, and ISVs