Manager, Applied AI Engineering (Enterprise)

About the Team The Technical Success team helps OpenAI’s customers realize meaningful and sustained value from our technology. We partner with customers throughout their journey—from initial exploration and solution design to production implementation and organization-wide adoption. Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They combine deep technical judgment with strong customer instincts, translating frontier AI capabilities into secure, reliable systems and durable business outcomes. About the Role We are seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting our enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio. You will help your team identify high-value opportunities, design and deploy production-grade AI systems, navigate complex technical and organizational constraints, and expand successful implementations across workflows, teams, and business units. This role requires technical depth, people leadership, customer judgment, and operational rigor. You should be comfortable coaching engineers through architecture and evaluation decisions, engaging directly in high-stakes customer situations, and collaborating with Sales, Solutions Engineering, Product, Research, Engineering, Security, and Legal. You will also help define how we serve enterprise customers at scale by developing effective coverage models, reusable implementation patterns, technical enablement, escalation mechanisms, and systems for turning field insights into high-quality product feedback. In This Role, You Will - Build, manage, and develop a high-performing team of Applied AI Engineers supporting large and complex enterprise customers. - Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion. - Coach the team through decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost. - Establish an operating model for prioritizing accounts and engagements according to customer needs, strategic value, technical complexity, and potential for repeatable impact. - Serve as a senior technical escalation point during critical launches, production incidents, complex integrations, and high-stakes customer decisions. - Partner with customer executives and technical leaders to connect implementation decisions to measurable business and operational outcomes. - Help customers progress from experimentation to production systems and sustained adoption across their organizations. - Partner closely with Sales and Solutions Engineering to create continuity throughout the customer lifecycle and maintain shared accountability for customer success. - Translate customer needs and recurring implementation challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams. - Identify scalable market patterns, distinguish them from bespoke requests, and advocate for investments that can benefit multiple customers. - Develop reusable architectures, evaluation methods, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio. - Establish mechanisms for measuring production implementations, adoption, customer outcomes, delivery quality, team capacity, and the impact of reusable work. - Hire thoughtfully, raise the technical and leadership bar, and foster a culture of accountability, curiosity, collaboration, inclusion, and continuous learning. - Represent OpenAI with credibility and sound judgment in conversations with senior customer and internal stakeholders. You Might Thrive in This Role If You - Have significant experience managing customer-facing technical teams, such as Applied AI Engineers, Solutions Architects, Forward Deployed Engineers, Customer Engineers, or Technical Account Managers. - Have built or led teams responsible for implementing complex software, data, machine learning, or AI systems in enterprise environments. - Maintain sufficient technical depth to evaluate architectures, ask incisive questions, challenge assumptions, and coach engineers through difficult implementation decisions. - Have experience taking AI, machine learning, or other technically complex systems from prototype to production. - Understand production-system requirements, including reliability, observability, security, privacy, data governance, evaluation, and operational readiness. - Have led teams through ambiguity, competing priorities, escalations, and rapidly evolving products or markets. - Can translate effectively among technical details, customer needs, product strategy, and business outcomes. - Have worked with large organizations involving multiple business units, stakeholder groups