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, procurement processes, or governance requirements.
- Demonstrate strong executive presence and can build trust with engineering leaders, business executives, security teams, and other senior stakeholders.
- Have designed operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes for a growing technical organization.
- Are a strong cross-functional partner who can navigate disagreement directly while maintaining trust and shared accountability.
- Use data and clear principles to allocate limited resources across a large portfolio of opportunities.
- Care deeply about developing people and have a track record of coaching team members, raising performance, and building inclusive teams.
- Are energized by helping organizations adopt frontier AI responsibly and turn emerging capabilities into durable value.
RELEVANT EXPERIENCE MAY INCLUDE
- Leading teams in applied AI engineering, solutions architecture, forward-deployed engineering, professional services, technical consulting, or customer engineering.
- Implementing generative AI, machine learning, developer platforms, cloud infrastructure, data platforms, or other complex enterprise technologies.
- Working with customers in semiconductors, media, entertainment, or similarly complex and technology-intensive industries.
- Supporting global customers, multi-business-unit implementations, regulated workflows, or large-scale organizational transformations.
- Building technical enablement, reusable solution patterns, evaluation frameworks, or customer implementation methodologies.
Direct experience in these industries is not required. We value leaders who can recognize common technical and organizational patterns while adapting their approach to different customer environments.