The Technical Success team helps OpenAI's customers realize meaningful and sustained value from our technology.
Applied AI Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams.
About the Role
Seeking a Manager to build, lead, and develop a high-performing team of Applied AI Engineers supporting enterprise customers.
Accountable for the technical success of a broad and strategically important customer portfolio.
Requires technical depth, people leadership, customer judgment, and operational rigor.
Hybrid work model of 3 days in the office per week; relocation assistance offered.
Responsibilities
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.
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 outcomes.
Help customers progress from experimentation to production systems and sustained adoption.
Partner closely with Sales and Solutions Engineering.
Translate customer needs into actionable feedback for Product, Research, Engineering, Security.
Develop reusable architectures, evaluation methods, playbooks, tooling, and enablement.
Hire thoughtfully and foster a culture of accountability, curiosity, collaboration, inclusion, and continuous learning.
Requirements
Significant experience managing customer-facing technical teams (Applied AI Engineers, Solutions Architects, Forward Deployed Engineers, Customer Engineers, or Technical Account Managers).
Experience building or leading teams implementing complex software, data, machine learning, or AI systems in enterprise environments.
Technical depth to evaluate architectures, ask incisive questions, challenge assumptions, and coach engineers.
Experience taking AI, machine learning, or other technically complex systems from prototype to production.
Understanding of production-system requirements: reliability, observability, security, privacy, data governance, evaluation, and operational readiness.
Experience leading teams through ambiguity, competing priorities, escalations, and rapidly evolving products or markets.
Strong executive presence and ability to build trust with engineering leaders, business executives, and security teams.