OpenAI Manufacturing Quality Engineer overseeing quality of data center equipment at supplier factories. Responsible for audits, monitoring production, coordinating with suppliers, and driving continuous improvement.
Responsibilities
As a Manufacturing Quality Engineer, you will oversee the quality of data center equipment at supplier factories. You will use production data, audits, and test results to identify systemic, recurring, or safety-related issues and work with suppliers to address them through Closed Loop Learning (CLL).
Manufacturing Monitoring and Supplier Improvement
Manufacturing monitoring: Work with Manufacturing Operations to monitor production progress, quality controls, inspection results, and test readiness. Flag emerging risks and coordinate a response with suppliers.
Product and process audits: Audit products and processes during and after production against engineering requirements, critical-to-quality (CTQ) characteristics, approved procedures, and quality standards. Document findings and track corrective actions to closure.
Manufacturing coordination: Agree on production checkpoints and inspection and testing requirements with suppliers, engineering, sourcing, supply chain, commissioning, and quality teams. Escalate risks to equipment acceptance or delivery.
Manufacturing scorecards: Develop supplier and product scorecards with Manufacturing Operations. Review audit findings, test results, recurring defects, and open issues with suppliers to prioritize improvements.
Drive continuous improvement: Lead the CLL process with suppliers. Track root cause analyses and corrective and preventive actions in a shared register. Verify that each action addresses the underlying problem before closing it.
Factory Acceptance Testing (FAT)
Standardize requirements and formats: Develop product-specific FAT requirements and standard test formats with equipment suppliers and OpenAI’s engineering, commissioning, quality, and Manufacturing Operations teams.
Define critical quality requirements: Document the CTQ characteristics each test must verify in an OpenAI-accepted format. Use CLL findings to revise FAT procedures so future tests check for known failure modes.
Ensure auditable supplier records: Require suppliers to retain test results and make them available for OpenAI audits.
Manage documentation and revision control: Review final FAT records and audit reports for each piece of equipment and maintain a controlled revision history.
Qualification
Bachelor’s degree in electricalAbility to develop test checklistsASQ Certified Quality EngineerWe are an equal opportunity employerFor additional information
Required
Bachelor’s degree in electrical, mechanical, or industrial engineering.
At least 10 years of data center industry experience spanning quality engineering and project management.
Experience coordinating FAT and FWT with suppliers and resolving equipment quality issues.
Ability to develop test checklists, define CTQs, review test results, and maintain auditable quality records.
Experience monitoring supplier production, auditing products and processes during and after production, and using scorecards to improve supplier and product quality. Experience managing controlled documents and deviations.
Ability to coordinate supplier schedules and plan inspections and tests across multiple pieces of equipment.
Ability to communicate quality requirements and coordinate decisions across suppliers, engineering, commissioning, sourcing, supply chain, manufacturing, operations, quality, and construction teams.
Willingness and ability to travel approximately 40–60% of the time to supplier manufacturing facilities and data center project sites.
Preferred
Technical knowledge of data center infrastructure, including mechanical, electrical, and controls systems.
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.
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.
