Program Quality Engineer

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 supporting the commissioning, ensuring operational readiness across our global portfolio.

About the Role

We are seeking a Manufacturing Quality Engineer focused on supplier manufacturing quality for data center equipment. The role proactively monitors manufacturing activities, audits products and processes during and after production, and uses manufacturing scorecards to drive issue closure and sustained supplier and product improvement. Factory Acceptance Testing (FAT), Factory Witness Testing (FWT), and deviation management support this broader responsibility for equipment quality, with complete, controlled, and auditable records.

The ideal candidate combines quality engineering and project management experience in the data center industry with an electrical, mechanical, or industrial engineering background. Success in this role requires close collaboration with suppliers and engineering, commissioning, sourcing, supply chain, construction , operation , and manufacturing teams to align equipment quality requirements, testing, and issue resolution.

Key Responsibilities

Manufacturing Monitoring and Supplier Improvement

• Manufacturing monitoring: In close collaboration with the Manufacturing & Operation Team proactively monitor supplier manufacturing activities and product quality throughout production. Review production progress, quality assurance & controls, inspection results, and test readiness to identify risks early and coordinate timely resolution.

• Product and process audits: Audit supplier products and manufacturing processes during manufacturing and after production to verify compliance with engineering requirements, CTQs, approved procedures, and quality standards. Document findings and track corrective actions through closure.

• Manufacturing coordination: Work closely with supplier manufacturing teams and internal engineering, sourcing, supply chain, commissioning, and quality teams to align production checkpoints, inspection and testing requirements, and corrective actions. Escalate manufacturing quality risks that could affect equipment acceptance or delivery.

• Manufacturing scorecards: In close collaboration with the Manufacturing & Operation Team develop and maintain supplier and product manufacturing scorecards to track quality performance, audit findings, test results, recurring defects, and issue closure. Review performance with suppliers and internal teams to identify priorities for improvement.

• Drive continuous improvement: Work closely with suppliers and engineering, commissioning, sourcing, supply chain, and manufacturing teams to address root causes, close quality issues, verify corrective-action effectiveness, and drive sustained supplier and product improvement.

Factory Witness Testing (FWT)

• Own and track FWT: Lead the process from initiation through completion across suppliers and the program. Maintain the equipment list and a comprehensive tracker covering every process step for each equipment item and supplier.

• Align checklists and stakeholders: Develop standardized FWT checklists with OAI subject matter experts, installing contractors, and the general contractor (GC). Incorporate each stakeholder’s requirements and secure agreement before testing begins.

• Coordinate pre-test planning: Conduct planning meetings two weeks before each scheduled FWT, accounting for manufacturer production schedules. Confirm test readiness and coordinate participant attendance and travel.

• Coordinate and conduct testing: Lead FWT activities at manufacturer facilities, limit attendance to essential participants, and ensure the designated BVMC representative attends the entire test, from kickoff through completion.

• Manage documentation and reporting: Obtain, review, and organize final FWT reports and supporting records from all relevant stakeholders.

Factory Acceptance Testing (FAT)

• Own and track FAT: Lead the process from initiation through completion across suppliers and the program. Maintain the equipment list and a comprehensive tracker covering every process step for each equipment item and supplier.

• Standardize requirements and formats: Develop product-specific FAT requirements and standardized test formats in close collaboration with equipment suppliers and OAI engineering, commissioning, and quality teams.

• Define critical quality requirements: Identify and document Critical-to-Quality (CTQ) characteristics for each equipment FAT, ensuring all applicable requirements are addressed in an OAI-accepted format.

• Ensure auditable supplier records: Ensure suppliers record and retain test results so they can be audited by OAI at any time.

• Manage documentation and revision control: Obtain, review, and organize final supplier FAT records, controlled revisions, and audit reports for each equipment item.

• Conduct periodic supplier audits: Verify that testing is performed correctly and test documentation is accurate and complete.

Deviation Management

• Assess short shipments and missing or failed tests in partnership with Manufacturing Operations.

• Coordinate supplier resources to support resolution at the project site.

• Track deviations and associated resolution activities through closure.

Qualifications

• Bachelor’s degree in electrical, mechanical, or industrial engineering.

• Minimum 10 years industry experience in quality engineering and project management within the data center industry.

• Experience working closely with suppliers to coordinate equipment testing, including FAT and FWT, and resolve quality issues.

• Ability to develop test checklists, define CTQs, review test results, and maintain auditable quality records.

• Experience monitoring supplier manufacturing, conducting product and process audits during and after production, and using manufacturing scorecards to drive issue closure and supplier and product improvement. Experience with document control and deviation management.

• Strong planning and coordination skills, including managing multiple suppliers, equipment items, and schedules.

• Experience collaborating with engineering, commissioning, sourcing, supply chain, and manufacturing teams, with a practical understanding of their roles and interfaces. Strong communication skills and the ability to align these teams with quality, suppliers, and construction stakeholders.

• Willingness and ability to travel approximately 40–60% of the time to supplier manufacturing facilities and data center project sites.

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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