Tech Lead, Deployment & Operations — Custom Infrastructure

About the Team OpenAI’s Hardware organization develops AI-native silicon and system-level solutions for the unique demands of advanced AI workloads. Building on efforts like Jalapeño, the team is developing future generations of AI-native silicon and tightly integrated systems to power the next generation of frontier models. By co-designing chips, systems, tools, and methodologies, the team helps deliver faster, more efficient, and production-ready hardware for OpenAI’s supercomputing platform. 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 leading through ambiguity, especially when the hardware, tooling, and operational model are still being built - Have strong judgment around deployment sequencing, technical risk, operational readiness, and when to escalate - Communicate clearly across technical and operational teams, and can align stakeholders through complex deployment and production issues - Care deeply about building practical systems, tools, and processes that work reliably at scale - Have a bias toward ownership and are comfortable jumping into urgent technical issues when needed Qualifications - 8+ years of engineering experience in hardware systems, infrastructure, data center deployment, production operations, systems engineering, silicon bring-up, or related technical domains - Strong technical depth in one or more of: hardware deployment, data center operations, rack-scale systems, silicon bring-up, systems validation, fleet operations, reliability engineering, infrastructure automation, or hardware/software integration - Experience bringing complex hardware systems from development or validation into production environments - Experience working closely with silicon, systems, software, infrastructure, networking, or data center teams - Experience with deployment planning, operational readiness, incident response, debugging, and root-

8+ years of engineering experience in hardware systems, infrastructure, data center deployment, production operations, systems engineering, silicon bring-up, or related technical domains. Strong technical depth in one or more of: hardware deployment, data center operations, rack-scale systems, silicon bring-up, systems validation, fleet operations, reliability engineering, infrastructure automation, or hardware/software integration. Experience bringing complex hardware systems from development or validation into production environments. Experience working closely with silicon, systems, software, infrastructure, networking, or data center teams. Experience with deployment planning, operational readiness, incident response, debugging, and root-cause analysis.

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.