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 Industrial Compute team ensures that datacenter infrastructure systems are designed, manufactured, and deployed with exceptional reliability, scalability, and performance.
We work closely with engineering teams, manufacturing partners, construction teams, and datacenter operations to ensure rack systems are built, validated, and deployed efficiently across our rapidly expanding global infrastructure footprint.
Our work spans product definition, design validation, manufacturing readiness, and field deployment—ensuring that rack infrastructure supports the performance, reliability, and operational needs of OpenAI’s compute platforms.
About the Role
We are seeking an experienced Rack Product Engineer to own the technical development, manufacturing readiness, and lifecycle performance of rack infrastructure deployed across OpenAI’s datacenters. They are the overall engineering subject matter expert for managing, test, quality, and manufacturing engineering responsible for scaling manufacturing operations and meeting on time delivery.
This role sits at the intersection of hardware design, manufacturing, supplier engagement, and datacenter deployment. You will work closely with compute, mechanical, power, and networking teams to define rack architectures and ensure they are manufacturable, scalable, and operationally reliable.
You will partner with contract manufacturers and suppliers to ensure rack systems are built to specification, while also working internally to drive design improvements, resolve field issues, and support rapid infrastructure deployment at global scale.
Travel
Domestic and international travel as needed (estimated 30%) to manufacturing sites, supplier facilities, and datacenter deployments.
Key Responsibilities
Own the technical definition and lifecycle management of rack infrastructure deployed across OpenAI datacenters.
Drive rack architecture decisions across mechanical structure, power distribution, cooling interfaces, and compute/network integration.
Translate system requirements into manufacturable rack-level designs capable of supporting large-scale global deployment.
Partner with design and manufacturing teams to ensure rack systems are optimized for manufacturability, assembly, serviceability, and datacenter installation.
Support New Product Introduction (NPI) activities including prototype builds, pilot runs, and ramp-to-volume readiness.
Collaborate with rack manufacturers and component suppliers to ensure production builds meet design intent and deployment schedules.
Serve as the primary technical interface between OpenAI engineering teams and manufacturing partners.
Investigate and resolve rack-related issues encountered during manufacturing, integration, and datacenter deployment.
Lead cross-functional root cause analysis and drive design or process improvements to prevent recurring issues.
Partner with datacenter construction and operations teams to support deployment readiness, factory and site acceptance testing, and field issue resolution.
Coordinate with engineering, sourcing, manufacturing, and operations teams to align rack development with global infrastructure deployment schedules and maintain critical product documentation.
Qualifications
10+ years of experience in hardware product engineering, system integration, manufacturing engineering, or datacenter infrastructure engineering.
Bachelor's degree in Mechanical Engineering, Electrical Engineering, Systems Engineering, or a related field (or equivalent experience).
Experience developing and deploying rack-level infrastructure for compute systems or datacenters.
Demonstrated ability to drive cross-functional technical programs from concept through manufacturing and deployment.
Strong analytical and problem-solving skills with experience resolving complex hardware integration issues.
Preferred Skills
Experience with hyperscale datacenter infrastructure or large-scale compute deployments.
Deep familiarity with rack architectures, liquid cooling, power distribution systems, and compute integration.
Experience working with ODMs, JDMs, or contract manufacturers.
Knowledge of design for manufacturing (DFM) and design for assembly (DFA) principles.
Experience supporting NPI programs and hardware ramp-to-volume production.
Lean Six Sigma or equivalent process improvement training.
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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