Manager, AI Deployment Engineering — Enterprise (ProServe, Media, Telco, Private Equity)

About The Team

The Technical Success team is responsible for helping OpenAI’s customers realize meaningful and sustained value from our technology. We partner closely with customers throughout their deployment journey, helping them move from initial exploration to production applications and broader organizational adoption.

The Enterprise AI Deployment Engineering team supports complex organizations across Professional Services, Media and Entertainment, Telecommunications, and Private Equity. These customers operate in varied environments—from global consulting and legal organizations to consumer media platforms, telecommunications providers, and private equity portfolios—but share a need to deploy AI securely, reliably, and at scale.

AI Deployment Engineers serve as trusted technical partners to customer executives, engineering teams, product leaders, security organizations, and transformation teams. They bring deep technical judgment, strong customer instincts, and the ability to translate frontier model capabilities into durable business outcomes.

About The Role

We are seeking a Manager to build, lead, and develop a team of AI Deployment Engineers supporting OpenAI’s Enterprise customers. You will be accountable for the technical success of a broad and strategically important customer portfolio.

• Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion.
• Coach the team through complex decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost.
• Establish a clear operating model for prioritizing accounts and engagements based on customer need, strategic value, technical complexity, and the 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 deployment decisions to measurable business and operational outcomes.
• Help customers progress from isolated experimentation to production deployments and sustained adoption across teams, workflows, and business units.
• Work closely with Sales and Solutions Engineering to create continuity across the customer lifecycle and maintain shared accountability for customer success.
• Translate customer needs and recurring deployment challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams.
• Distinguish scalable market patterns from bespoke requests and advocate for investments that can benefit multiple customers.
• Develop reusable architectures, evaluation approaches, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio.
• Create mechanisms to measure production deployments, usage, adoption, customer outcomes, delivery quality, team capacity, and the impact of reusable work.
• Hire thoughtfully, raise the technical and leadership bar of the organization, and foster a culture of accountability, curiosity, collaboration, and continuous learning.
• Represent OpenAI with credibility and sound judgment in conversations with senior customer and internal stakeholders.

Qualifications

• Significant experience managing customer-facing technical teams, such as Solutions Architects, Deployment Engineers, Forward Deployed Engineers, Technical Account Managers, or similar functions.
• Built or led teams responsible for deploying complex software, data, machine learning, or AI systems in enterprise environments.
• Maintain enough technical depth to evaluate architectures, ask incisive questions, challenge assumptions, and coach engineers through difficult implementation decisions.
• Experience taking AI, machine learning, or other technically complex systems from prototype to production.
• Understand the requirements of production systems, including reliability, observability, security, privacy, data governance, evaluation, and operational readiness.
• Led teams through ambiguity, competing priorities, escalations, and rapidly changing products or markets.
• Translate between technical details, customer needs, product strategy, and business outcomes.
• Work with large, complex organizations that include multiple business units, stakeholder groups, procurement processes, or governance requirements.
• Build strong executive presence and can build trust with engineering leaders, business executives, security teams, and other senior stakeholders.
• Design operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes for a growing technical organization.
• 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 the opportunity to help organizations adopt frontier AI responsibly and translate emerging capabilities into durable value.

What You’ll Get to Work On

• Build, manage, and develop a high-performing team of AI Deployment Engineers supporting enterprise customers across Professional Services, Media and Entertainment, Telecommunications, and Private Equity.
• Own the quality and impact of the team’s work across solution design, implementation, production readiness, adoption, and expansion.
• Coach the team through complex decisions involving architecture, model selection, evaluations, reliability, latency, safety, security, governance, and cost.
• Establish a clear operating model for prioritizing accounts and engagements based on customer need, strategic value, technical complexity, and the 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 deployment decisions to measurable business and operational outcomes.
• Help customers progress from isolated experimentation to production deployments and sustained adoption across teams, workflows, and business units.
• Work closely with Sales and Solutions Engineering to create continuity across the customer lifecycle and maintain shared accountability for customer success.
• Translate customer needs and recurring deployment challenges into actionable feedback for Product, Research, Engineering, Security, and other internal teams.
• Distinguish scalable market patterns from bespoke requests and advocate for investments that can benefit multiple customers.
• Develop reusable architectures, evaluation approaches, playbooks, tooling, and enablement that improve time to value across the enterprise portfolio.
• Create mechanisms to measure production deployments, usage, adoption, customer outcomes, delivery quality, team capacity, and the impact of reusable work.
• Hire thoughtfully, raise the technical and leadership bar of the organization, and foster a culture of accountability, curiosity, collaboration, and continuous learning.
• Represent OpenAI with credibility and sound judgment in conversations with senior customer and internal stakeholders.

OpenAI

We are an AI research and deployment company dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity. We push the boundaries of the capabilities of AI systems and seek to safely deploy them to the world through our products. AI is an extremely powerful tool that must be created with safety and human needs at its core, and to achieve our mission, we must encompass and value the many different perspectives, voices, and experiences that form the full spectrum of humanity.

We are an equal opportunity employer, and we do not discriminate on the basis of race, religion, color, national origin, sex, sexual orientation, age, veteran status, disability, genetic information, or other applicable legally protected characteristic.