Partner AI Deployment Engineer - Aws

OpenAI OpenAI · AI Frontier · India · Remote · Go To Market

This role focuses on enabling the deployment and scaling of OpenAI's Generative AI applications through a strategic partnership with AWS. The engineer will act as a senior technical advisor to AWS field leadership, guiding customers from ideation to production, and enabling AWS partners to independently drive deployments. Responsibilities include shaping strategy, designing end-to-end AI architectures, building prototypes, establishing best practices, and enabling the AWS ecosystem through workshops and reusable assets. The role requires strong technical leadership, strategic influence, and the ability to build repeatable systems for scaled adoption.

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
  • Experience managing C-level technical and business relationships with complex global organizations
  • Deep technical expertise in AI/ML deployment
  • Strong judgment and strategic thinking
  • Ecosystem leadership and enablement
  • Solution architecture design
  • Prototype development
  • Understanding of scalable, secure, and production-ready GenAI systems
  • Experience with AWS services

Nice to have

  • Experience with OpenAI products
  • Experience working with AWS field teams (Solutions Architects, Specialists, Partner teams)
  • Experience enabling partners (GSIs, RSIs, ISVs)

What the JD emphasized

  • primary technical counterpart to AWS field leadership
  • shape strategy, define engagement models, and build repeatable systems
  • guiding complex enterprise customers from ideation to production
  • enabling AWS and partners to independently drive deployments
  • senior technical counterpart
  • Influence joint account strategy and technical direction
  • defining engagement models, prioritization frameworks, and best practices
  • Lead technical strategy for large, ambiguous, and high-stakes enterprise engagements
  • Guide customers from early ideation through architecture design, prototyping, and production deployment
  • technical decision-maker and escalation point
  • Apply strong judgment to prioritize opportunities and allocate limited technical resources
  • 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
  • Partner closely with Alliances, Product, Engineering, GTM, and Enablement
  • Act as a bridge between field and product
  • Contribute to internal knowledge systems and help define standards, patterns, and playbooks
  • 8+ years of technical consulting (or equivalent) experience, managing C-level technical and business relationships with complex global organizations.
  • Operate as a technical leader and systems thinker, not just an individual contributor.
  • 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.
  • Are comfortable owning ambiguous, high-visibility problem spaces.
  • Take a long-term, ecosystem-oriented view of impact.
  • Are motivated by 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, and building repeatable systems
  • 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
  • enable AWS and partners through scalable technical motions
  • develop reusable solution patterns and assets
  • mentor and uplift partner technical teams