About the role
About
the Team OpenAI’s HLS AI Success Engineering team partners with the world’s most ambitious healthcare and life sciences organizations to translate cutting edge AI into real patient outcomes. We guide customers from first deployment through scaled enterprise adoption. Our work spans technical integration and enablement, workflow transformation, and sustained program and product delivery. Our customers range from fast-growing healthcare and life sciences innovators to the world’s largest biopharma, medical technology, healthcare provider, payer, and research organizations. Every engagement is an opportunity to shape how AI accelerates scientific innovation, transforms healthcare delivery, and improves patient outcomes.This role sits at the center of our mission.
About
the Role 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. You will work closely with Sales, Solutions Architecture, Product, and Research to ensure the customer experience is connected and successful across every touchpoint. Success in this role means accelerating adoption, increasing customer activation depth, guiding strategic use cases that get to production, and helping customers demonstrate tangible impact. This role is based in San Francisco or NYC, with a hybrid schedule of 3 days per week in the office, or can be performed remotely from anywhere in the U.S. We also provide relocation support for new employees. In this role, you will: 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 Guide value realization and measure impact through baselines, KPI definition, and post deployment reporting Facilitate workshops on use case design, adoption best practices, champion building, and internal enablement Help drive expansions by identifying high leverage opportunities where OpenAI’s platform can power new workflows or lines of business Serve as the technical advisor for existing customer implementations by guiding and optimizing account setup, configuration, etc. You’ll thrive in this role if you: 5+ 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 Meaningful experience working with healthcare or life-sciences organizations - such as providers, payers, biopharma, medical-device companies, CROs, or health-technology organizations - and an understanding of their data, workflows, regulatory environments, and operating models. Scientific or clinical training in a relevant field such as medicine, biology, chemistry, pharmacy, biomedical engineering, or public health, with a passion for applying AI responsibly to advance scientific innovation and improve patient outcomes. 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 deploying technology in regulated enterprise environments, including authentication, access controls, encryption, data classification, retention, auditability, and incident response. Working knowledge of healthcare and life-sciences
