O

OpenAI

Builds AI models and the ChatGPT assistant

Engineering Manager - Client Platform Engineering

Engineering LeadershipConfirmed live in the last 24 hours
Full-timeSan Francisco, CA, USA

About the Job

Requirements

  • Built and led teams that owned secure, reliable, mission-critical services and infrastructure at scale, from strategy through production operations.
  • Delivered internal platforms, tooling, and services that materially improved reliability, security, and employee experience.
  • Made sound software and infrastructure engineering decisions at scale; deep endpoint expertise is strongly preferred.
  • Raised production readiness through direct technical review of architecture, automation, code, infrastructure as code/GitOps, continuous integration/continuous delivery, observability, and operational tradeoffs.
  • Operated infrastructure with material security or identity risk through staged rollouts, incidents, and decisions balancing risk, compliance, and employee or developer experience.
  • Committed to joining the team’s engineering on-call rotation after ramp-up and using firsthand operational context to improve reliability and reduce toil.
  • Built inclusive teams, communicated with clarity and candor, and influenced partners across Security, IT, and Product/Engineering.

Responsibilities

  • Lead and develop a high-performing engineering team; hire thoughtfully, coach engineers, create clarity, and foster an inclusive, high-accountability culture.
  • Define and execute a multi-year client-platform strategy and roadmap across macOS, Windows, iOS, Android, and Linux, including how Codex and agents can reshape employee computing.
  • Provide technical direction for endpoint posture, device trust, application delivery, device onboarding, updates, fleet telemetry, workflow orchestration, and employee-facing remediation. Lead the team to rethink the platform as Codex and agent capabilities advance, determining what software to build, what agents can own end to end, and which employee workflows can be eliminated.
  • Guide architecture and engineering tradeoffs across first-party services, open-source tooling, software-as-a-service platforms, infrastructure as code/GitOps, continuous integration/continuous delivery, and cloud infrastructure. Decide what to build, buy, standardize, retire, or redesign as AI changes platform capabilities.
  • Establish clear goals, ownership, planning, design reviews, and execution rhythms that enable the team to move quickly without sacrificing quality.
  • Improve reliability and evidence-backed security through observability, drift detection, staged rollouts, release gates, rollback paths, incident learning, runbooks, and operational ownership. Use telemetry to identify friction, measure outcomes, and improve systems before issues become tickets.
  • Partner with Security, IT, Research, Applied, Product, and specialized engineering teams to align priorities and implement company-wide changes, dogfood OpenAI products in real employee workflows, and continuously improve internal platforms.
  • Balance security and compliance controls with developer velocity, employee experience, and operational simplicity. Define where agents can act, where humans approve, and how actions are evaluated, audited, and reversed.
  • Use adoption, reliability, evidence-backed security posture, data freshness, employee experience, workflow completion, friction, agent effectiveness, and operational-load metrics to steer investment and communicate impact.
  • Partner with IT and Security teams to increase CPE’s impact across employee experience, security posture, and operational scale.

Desired Qualifications

  • Deep experience with one or more client-platform tool ecosystems such as Jamf, Intune, Android Enterprise, FleetDM/osquery, Munki/AutoPkg, or Linux configuration management.
  • Experience building internal platforms or services for application delivery, device posture or trust, onboarding, notifications, workflow orchestration, or fleet telemetry.
  • Familiarity with cloud infrastructure, Terraform, Kubernetes or containers, service orchestration, and large-scale observability.
  • Experience partnering with security, compliance, or privacy teams in high-assurance environments.
  • Experience supporting research, developer, robotics, hardware-lab, or other specialized computing environments.
  • A record of contributing to open-source tooling, engineering communities, or cross-company technical standards.

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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