O

OpenAI

Builds AI models and the ChatGPT assistant

Tech Lead – Deployment & Operations - Custom Infrastructure

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA$342k - $445k /yrHybrid

About the Job

Requirements

  • At least 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 for production systems.
  • Experience building tooling, automation, observability, or operational processes that improve deployment quality and fleet reliability.
  • Demonstrated ability to hire, develop, and lead senior technical talent.
  • Ability to move fluidly between people leadership, technical strategy, and hands-on operational problem solving.
  • Experience working in fast-moving environments.
  • Candidates may need to meet legal status requirements under U.S. export control laws and regulations.

Responsibilities

  • Lead a team responsible for deployment and operations of 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 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 an engineering culture grounded in ownership, technical rigor, operational excellence, and high-velocity execution.
  • Ensure custom hardware platforms can be deployed and operated reliably, repeatably, and safely at scale.
  • Contribute to and technically drive the architecture and design of future machine learning systems.

About the Company

OpenAI

Builds AI models and the ChatGPT assistant

OpenAI researches and builds artificial intelligence models and turns them into products for people, developers, and businesses, with a stated mission of making sure artificial general intelligence benefits all of humanity. Its launch of ChatGPT in 2022 brought generative AI into everyday use. People use ChatGPT to ask questions, write, code, and analyze files, developers build OpenAI's models into their own apps through its API, and its Codex agent works through coding tasks on its own. OpenAI earns money from ChatGPT subscriptions, business plans, and API usage. Sam Altman, Elon Musk, and others co-founded it in 2015; it is based in San Francisco and overseen by a nonprofit, the OpenAI Foundation.

Company size
1,001-5,000
Company stage
Late Stage VC
Total funding
$207.5B
Headquarters
San Francisco, CA
Founded
2015

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