Manager, AI Deployment Engineering - Codex

OpenAI OpenAI · AI Frontier · London, United Kingdom · Go To Market

Manager for AI Deployment Engineering focused on the Codex product, responsible for leading a team that helps customers integrate and scale AI coding tools into their software development lifecycle. The role involves technical leadership, customer engagement strategy, and partnering with product and research teams to drive adoption and gather feedback.

What you'd actually do

  1. Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts.
  2. Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption.
  3. Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures.
  4. Act as the senior technical escalation point for complex customer implementations and deployment challenges.
  5. Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities.

Skills

Required

  • 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering.
  • 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers.
  • Experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments.
  • Hands-on technical experience with software development systems and programming languages such as Python or JavaScript.
  • Understanding of modern software development lifecycles and how AI tooling transforms developer productivity and workflows.
  • Effective communication skills to translate complex technical and business topics to both engineering teams and executive stakeholders.
  • Ability to thrive in ambiguous, fast-moving environments and enjoy building new operating models and teams from first principles.
  • Strong ownership, humility, and a commitment to helping both customers and teammates succeed.

What the JD emphasized

  • production adoption
  • enterprise-scale
  • scalable deployment architectures
  • production environments
  • AI-enhanced development workflows

Other signals

  • customer adoption
  • production rollout
  • enterprise-scale