
Manager, Applied AI Engineering (Enterprise)
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Job description
About the Position
Manager, Applied AI Engineering (Enterprise)
New York City
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.
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 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.
Requirements
- Significant experience managing customer-facing technical teams.
- Experience building or leading teams responsible for implementing complex software, data, machine learning, or AI systems in enterprise environments.
- Sufficient 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.
- Understanding of production-system requirements, including reliability, observability, security, privacy, data governance, evaluation, and operational readiness.
- Experience leading teams through ambiguity, competing priorities, escalations, and rapidly evolving products or markets.
- Ability to translate effectively among technical details, customer needs, product strategy, and business outcomes.
- Experience working with large organizations involving multiple business units, stakeholder groups, procurement processes, or governance requirements.
- Strong executive presence and ability to build trust with engineering leaders, business executives, security teams, and other senior stakeholders.
- Experience designing operating models, coverage strategies, prioritization frameworks, or repeatable delivery processes for a growing technical organization.
- Strong cross-functional partnership skills, navigating disagreement directly while maintaining trust and shared accountability.
- Ability to use data and clear principles to allocate limited resources across a large portfolio of opportunities.
- Deep care for developing people and a track record of coaching team members, raising performance, and building inclusive teams.
- Enthusiasm for 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.
We Offer
- Opportunity to work with a leading AI research and deployment company.
- Be part of a mission-driven team dedicated to ensuring that general-purpose artificial intelligence benefits all of humanity.
- Competitive compensation and benefits package.
- Opportunity to shape the future of technology.
About the Company
OpenAI is 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.
For additional information, please see OpenAI’s Affirmative Action and Equal Employment Opportunity Policy Statement.
Background checks for applicants will be administered in accordance with applicable law, and qualified applicants with arrest or conviction records will be considered for employment consistent with those laws, including the San Francisco Fair Chance Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, and the California Fair Chance Act, for US-based candidates. For unincorporated Los Angeles County workers: we reasonably believe that criminal history may have a direct, adverse and negative relationship with the following job duties, potentially resulting in the withdrawal of a conditional offer of employment: protect computer hardware entrusted to you from theft, loss or damage; return all computer hardware in your possession (including the data contained therein) upon termination of employment or end of assignment; and maintain the confidentiality of proprietary, confidential, and non-public information. In addition, job duties require access to secure and protected information technology systems and related data security obligations.
To notify OpenAI that you believe this job posting is non-compliant, please submit a report through this form. No response will be provided to inquiries unrelated to job posting compliance.
We are committed to providing reasonable accommodations to applicants with disabilities, and requests can be made via this link.
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Label Your Data provides secure and high quality data annotation services for Computer Vision or NLP applications since 2020. We help Data Scientists and AI Engineers streamline the dataset labeling and focus on model development.About Label Your Data:— Founded in 2020;— 200+ annotation experts in Europe, LATAM and Africa;— 98%+ annotation accuracy benchmark;— 55 supported languages;— PCI/DSS certified;— ISO/IEC 27001:2013 certified;— GDPR, CCPA and HIPAA-compliant;— HQs in North America, EU and Asia.Our experience spans over 20 industries including Automotive, Robotics, Agriculture, E-commerce, Retail, Healthcare, Manufacturing, Fintech and Insurance.Our core services include but are not limited to:— Image & video annotation: 2D boxes, OCR, object/action detection, polygons, key points, semantic segmentation, 3D cuboids;— Text annotation: classification, NER, intent & sentiment analysis, prompts creation, Q&A pairs generation;— Audio annotation: transcription, sentiment recognition;— Sensor data annotation;— Data classification & categorization;— Data entry;— Data collection;— Model validation.
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