Partner AI Deployment Engineer - Aws

OpenAI OpenAI · AI Frontier · Seoul, South Korea · Go To Market

This role focuses on enabling the deployment of Generative AI applications for developers and enterprises, primarily through strategic partnerships with AWS. The engineer will act as a technical advisor, guiding customers from experimentation to production-scale AI systems, shaping strategy, defining engagement models, and building repeatable systems. The role involves pre- and post-sales activities, leading technical strategy for complex engagements, designing AI architectures leveraging OpenAI and AWS services, and enabling AWS and partners 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. Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements.
  3. Design and communicate end-to-end AI architectures leveraging OpenAI and AWS services.
  4. Enable AWS and partners through scalable technical motions (workshops, playbooks, reference architectures, demos).
  5. Partner closely with Alliances, Product, Engineering, GTM, and Enablement to align on strategy and execution.

Skills

Required

  • 8+ years of technical consulting experience
  • managing C-level technical and business relationships
  • deep technical expertise in AI/ML
  • strong judgment
  • ecosystem leadership
  • designing and communicating end-to-end AI architectures
  • building and guiding development of prototypes, POCs, and reference implementations
  • establishing best practices for scalable, secure, and production-ready GenAI systems
  • enabling technical teams through workshops, playbooks, and reference architectures

Nice to have

  • experience with AWS services
  • experience with OpenAI models
  • experience with partner ecosystems (GSIs, RSIs, ISVs)

What the JD emphasized

  • primary technical counterpart to AWS field leadership
  • shape strategy, define engagement models, and build repeatable systems that scale
  • guiding complex enterprise customers from ideation to production
  • enabling AWS and partners to independently drive deployments
  • senior technical counterpart
  • technical leader and systems thinker
  • hands-on building with strategic influence and scale
  • owning ambiguous, high-visibility problem spaces
  • ecosystem-oriented view of impact
  • driving customer and partner success at scale

Other signals

  • driving customer outcomes through AWS and partner ecosystems
  • shaping strategy, defining engagement models, and building repeatable systems that scale
  • guiding complex enterprise customers from ideation to production
  • enabling AWS and partners to independently drive deployments