OpenAI· Hardware· San Francisco
Tech Lead, Deployment & Operations — Custom Infrastructure
Comp$342K – $445K
Classified Tasks (14)
Automate 0%Augment 43%Human-Only 57%
Augment (6)
AI assists, human decides
Build operational processes, technical workflows, tooling, and cross-functional alignment required to deploy and operate custom AI hardware in OpenAI’s supercomputing infrastructure
operational
Define deployment processes, operational playbooks, technical readiness criteria, escalation paths, and reliability practices for new hardware platforms
operational
Conduct architecture reviews, deployment planning, failure analysis, operational debugging, and critical system-level decision-making
technical
Identify gaps in tooling, observability, automation, validation coverage, and operational processes, and build plans to close them
analytical
Establish clear metrics for deployment readiness, reliability, performance, maintainability, and operational health
analytical
Contribute to and drive the technical architecture and design of future ML systems
technical
Human-Only (8)
Requires human judgment
Serve as the Directly-Responsible Individual for bringing custom silicon and associated systems into data center environments, ensuring deployment, bring-up, validation, operational readiness, and ongoing reliability at scale
leadership
Lead deployment and operations of OpenAI’s custom silicon and systems in data center environments
leadership
Own the path from hardware bring-up and validation through production deployment, operational readiness, and sustained fleet support
operational
Lead a team focused on transitioning new hardware platforms from lab validation into production data center deployment
leadership
Partner with silicon, systems, software, infrastructure, networking, data center, supply chain, and external partner teams to ensure successful deployment at scale
communication
Drive cross-functional execution across lab bring-up, rack/system integration, data center deployment, fleet monitoring, debugging, and issue resolution
operational
Ensure custom hardware platforms can be deployed and operated reliably, repeatably, and safely at scale
operational
Mentor and develop engineers while maintaining deep engagement in technical execution
leadership
Job description
Tech Lead, Deployment & Operations — Custom Infrastructure | OpenAI Careers ## Tech Lead, Deployment & Operations — Custom Infrastructure Hardware - San Francisco Apply now(opens in a new window) ## **About the Team** OpenAI’s Hardware organization develops silicon and system-level solutions designed for the unique demands of advanced AI workloads. The team is responsible for building the next generation of AI-native silicon while working closely with software and research partners to co-design hardware tightly integrated with AI models. In addition to delivering production-grade silicon for OpenAI’s supercomputing infrastructure, the team also creates custom design tools and methodologies that accelerate innovation and enable hardware optimized specifically for AI. ## **About the Role** We are seeking a Technical Lead to lead deployment and operations for OpenAI’s Silicon & Systems team. This person will become the Directly-Responsible Individual responsible for bringing OpenAI’s custom silicon and associated systems into data center environments, ensuring successful deployment, bring-up, validation, operational readiness, and ongoing reliability at scale. This role sits at the intersection of silicon, systems, infrastructure, data center operations, and software. You will lead a team focused on taking new hardware platforms from lab validation into production data center deployment. You will be responsible for building the operational processes, technical workflows, tooling, and cross-functional alignment required to deploy and operate custom AI hardware reliably in OpenAI’s supercomputing infrastructure. The ideal candidate is both a strong leader and a deeply technical operator. You should be comfortable staying close to the technical details of hardware bring-up, fleet deployment, debugging, system validation, data center integration, and production operations. This role requires strong execution, excellent cross-functional judgment, and the ability to drive clarity in ambiguous, fast-moving environments. ## **In this role, you will:** * Lead a team responsible for deployment and operations of OpenAI’s custom silicon and systems in data center environments * Own the path from hardware bring-up and validation through production deployment, operational readiness, and sustained fleet support * Partner closely with silicon, systems, software, infrastructure, networking, data center, supply chain, and external partner teams to ensure successful deployment at scale * Define deployment processes, operational playbooks, technical readiness criteria, escalation paths, and reliability practices for new hardware platforms * Drive cross-functional execution across lab bring-up, rack/system integration, data center deployment, fleet monitoring, debugging, and issue resolution * Stay hands-on technically through architecture reviews, deployment planning, failure analysis, operational debugging, and critical system-level decision-making * Identify gaps in tooling, observability, automation, validation coverage, and operational processes, and build plans to close them * Establish clear metrics for deployment readiness, reliability, performance, maintainability, and operational health * Build a strong engineering culture grounded in ownership, technical rigor, operational excellence, and high-velocity execution * Ensure OpenAI’s custom hardware platforms can be deployed and operated reliably, repeatably, and safely at scale * Be a contributor and technical driver for the architecture and design of future ML systems ## **You might thrive in this role if you:** * Enjoy mentoring and developing engineers while staying deeply engaged in technical execution * Are excited by the challenge of bringing new custom hardware platforms into real-world production data center environments * Can operate across silicon, systems, software, infrastructure, and data center operations * Are comfortable l