About the role
About the Team
OpenAI, in partnership with our capital and technology partners, is building a global network of advanced datacenters to support the most demanding AI workloads. The Infrastructure Quality team ensures that all datacenter systems are manufactured, delivered, and commissioned to the highest standards of quality, reliability, and performance.
We work closely with manufacturing partners, general contractors, engineering teams, and operations staff to ensure that every component is delivered ready for installation, startup, and long-term service. Our work spans from vendor qualification through commissioning, ensuring operational readiness across our global portfolio.
About the Role
We are seeking an experienced Manufacturing Quality Engineer (MQE) to establish, implement, and manage a manufacturing-focused quality program for datacenter infrastructure. This role will be responsible for vendor oversight, quality assurance, process improvement, and issue resolution for all critical systems.
You will lead vendor audits, monitor performance metrics, and coordinate corrective actions to ensure predictable delivery schedules, reduced risks, and operational reliability. By partnering with vendors, construction teams, and internal stakeholders, you will help ensure OpenAI’s datacenters are delivered on time and built to the highest operational standards.
Travel
Domestic and international travel as needed (estimated 40–60%) to manufacturing sites, datacenter locations, and partner facilities.
Key Responsibilities
Vendor Oversight & Performance Management
Conduct manufacturing evaluation, audits, and improve vendor performance across production, inspection, testing, and delivery phases.
Develop and track quality metrics to assess manufacturing performance and identify trends.
Partner with vendors to refine processes, training, and quality controls to mitigate risks before shipment.
Program Development & Execution
Develop and maintain a datacenter-focused manufacturing quality program that supports global deployment schedules.
Integrate manufacturing quality requirements into sourcing, design, and construction processes.
Establish effective cross-functional communication between manufacturing sites, construction teams, and operations.
Quality Leadership & Collaboration
Provide guidance to vendor and contractor quality teams, ensuring adherence to OpenAI’s standards and specifications.
Collaborate with engineering, sourcing, construction, and operations to align quality processes with project goals.
Mentor vendor teams and provide structured feedback to drive continuous improvement.
Issue Resolution & Continuous Improvement
Audit quality activities at vendor and project sites to verify compliance with requirements.
Lead corrective and preventive action plans for audit findings and quality nonconformances.
Facilitate root cause analysis for recurring manufacturing issues and drive systemic process improvements.
Schedule & Documentation Management
Monitor manufacturing schedules to ensure on-time delivery to datacenter sites.
Ensure testing and inspection documentation is complete, accurate, and aligned with project milestones.
Participate in project quality, commissioning, and operational readiness meetings.
Qualifications
10+ years in manufacturing quality management, supplier quality engineering, process improvement, or datacenter engineering/operations.
Bachelor’s degree in engineering, manufacturing, construction management, or related field (or equivalent work experience).
Demonstrated ability to analyze data, solve problems, and improve manufacturing processes.
Proven track record managing deliverables for complex projects or supplier programs.
Strong communication skills with experience influencing both technical and executive audiences.
Preferred Skills
Technical knowledge of datacenter infrastructure systems, including mechanical, electrical, and controls components.
Experience in supplier performance management for mission-critical facilities.
ASQ Certified Quality Engineer, Quality Manager, or Quality Auditor.
PMP or equivalent project management certification.
Experience in industrial or high-volume manufacturing environments.
About OpenAI
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.
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