AI Success Engineer

OpenAI OpenAI · AI Frontier · Munich, Germany · Go To Market

AI Success Engineer role focused on partnering with enterprise customers to drive adoption and business value from OpenAI's AI platform. This post-sales role involves technical leadership, customer advisory, and influencing product development by translating customer needs and feedback.

What you'd actually do

  1. Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization
  2. Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio
  3. Conduct technical enablement and configuration sessions across our broad product portfolio
  4. Identify and validate use cases by embedding with customer teams to understand workflows and pain points
  5. Lead account level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning

Skills

Required

  • Technical customer facing experience (TAM, consulting, SA, delivery)
  • Hands-on knowledge of OpenAI products, APIs, SDKs
  • Understanding of model behavior, limitations, technical tradeoffs
  • Knowledge of embeddings, retrieval augmentation, fine-tuning, custom model usage
  • Translate technical concepts to business language
  • Embed with customers to map workflows and diagnose adoption challenges
  • Project and program management
  • C-level stakeholder engagement
  • High ownership, fast decision making, context switching

Nice to have

  • GenAI consulting or deployment roles
  • Solutions architecture
  • Technical delivery leadership
  • Deep technical enterprise adoption work

What the JD emphasized

  • 8+ years of experience in technical customer facing roles such as technical account management, technical GenAI consulting or deployment roles, solutions architecture, technical delivery leadership, or deep technical enterprise adoption work
  • Deep, hands-on knowledge of OpenAI product capabilities, APIs, SDKs, connectors, and common integration patterns and able to explain model behavior, limitations, technical tradeoffs, embeddings, retrieval augmentation, and approaches to fine-tuning or custom model usage.
  • Have a strong record of driving technical deployments with hands-on on customer work and owning impactful adoption and value for large enterprise customers with complex environments and multiple stakeholders

Other signals

  • post-sales customer engagement
  • driving adoption and value realization
  • technical integration and enablement
  • workflow transformation
  • product delivery