About the job
The AI Success Engineer role is the primary post-sales point of contact for OpenAI’s most important customers. You are responsible for driving account health and adoption, ensuring technical readiness, identifying new use cases, and delivering measurable value to our customers with OpenAI’s ambitiously growing platform. This role blends technical depth, program management, customer advisory, and product influence. You will partner deeply with customer teams, map workflows, lead configuration, oversee deployment plans, and guide customers toward high impact use cases that showcase the full value of our platform.
Responsibilities
Lead the technical relationship for post-sale customers and act as their trusted advisor on deployment, adoption, and value realization
Own account health, adoption velocity, and ongoing technical deployment and success across your portfolio
Be an expert in all of OpenAI products across our API and agentic platform, Codex, ChatGPT Enterprise, and more and conduct technical enablement and configuration sessions across them
Identify and validate use cases by embedding with customer teams to understand workflows and pain points
Lead account level coordination across multiple workstreams, including new product activation, change management, and customer rollout and deployment planning
Build strong relationships with executive sponsors and technical stakeholders and help align business goals with OpenAI capabilities
Translate customer objectives into an actionable adoption roadmap with clear sequencing, milestones, and KPIs
Partner with Solutions Architecture, Product, Engineering and Research by surfacing customer feedback, field patterns, and technical blockers and act as a cross functional navigator who keeps teams aligned, informed, and moving toward customer outcomes
Qualifications
Minimum
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, customer architecture or engineering, or other deep technical enterprise adoption work
Deep, hands-on operational 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.
Practical experience with authentication and enterprise security concepts (SSO, domain verification, encryption, and enterprise compliance frameworks (GDPR, HIPAA, etc.)).
Understanding and familiarity with coding languages like Python or JavaScript, and comfort with REST APIs, SDKs, automation, CI/CD, containers, and cloud platforms.
Can translate technical concepts into clear business language and help customers understand the strategic impact of AI technologies
Can show 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
Are comfortable embedding with customers to map workflows, identify requirements, and diagnose adoption challenges
Have excellent project and program management instincts and can lead multi workstream initiatives with clarity and structure
Enjoy being a thought partner for C level stakeholders while also diving deep with technical teams
Operate with high ownership and can manage fast decision making, context switching, and dynamic customer needs
Preferred
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, customer architecture or engineering, or other deep technical enterprise adoption work
Deep, hands-on operational 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.
Practical experience with authentication and enterprise security concepts (SSO, domain verification, encryption, and enterprise compliance frameworks (GDPR, HIPAA, etc.)).
Understanding and familiarity with coding languages like Python or JavaScript, and comfort with REST APIs, SDKs, automation, CI/CD, containers, and cloud platforms.
Can translate technical concepts into clear business language and help customers understand the strategic impact of AI technologies
Can show 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
Are comfortable embedding with customers to map workflows, identify requirements, and diagnose adoption challenges
Have excellent project and program management instincts and can lead multi workstream initiatives with clarity and structure
Enjoy being a thought partner for C level stakeholders while also diving deep with technical teams
Operate with high ownership and can manage fast decision making, context switching, and dynamic customer needs
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