OpenAI· Go To Market· Munich, Germany
Manager, AI Deployment Engineering - Codex
Classified Tasks (17)
Automate 0%Augment 41%Human-Only 59%
Augment (7)
AI assists, human decides
Help customers move from experimentation to production by designing, implementing, and scaling real-world AI applications
technical
Partner directly with customer engineering teams to integrate Codex into development workflows from early experimentation and pilot design through enterprise-scale production rollout
technical
Ensure AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments
technical
Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures
technical
Deploy production-ready Codex solutions in customer environments
technical
Establish scalable deployment patterns, playbooks, technical patterns, and best practices to enable repeatable, scaled adoption of AI coding tools
operational
Synthesize insights from customer deployments and translate them into actionable feedback and product insights for internal teams
analytical
Human-Only (10)
Requires human judgment
Ensure the safe and effective deployment of OpenAI technologies across developers and enterprises
operational
Act as a trusted technical partner to customer teams to facilitate Codex adoption
communication
Manage a team of AI Deployment Engineers responsible for driving Codex adoption across strategic customers
leadership
Lead, hire, and onboard AI Deployment Engineers for the Codex deployment team
leadership
Mentor and coach engineers to develop technical capabilities and operate as trusted advisors to engineering leadership and executive stakeholders
leadership
Own the operating model and engagement strategy for Codex deployment efforts to move customers from pilot to production adoption
operational
Define and set technical strategy for deployment engagements operating at scale
leadership
Act as the senior technical escalation point for complex customer implementations and deployment challenges
technical
Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities
communication
Champion safe, reliable, and effective adoption of AI-powered development workflows across industries
leadership
Job description
Manager, AI Deployment Engineering - Codex | OpenAI Careers ## Manager, AI Deployment Engineering - Codex Go To Market - Munich, Germany Apply now(opens in a new window) ### **About the team** The AI Deployment Engineering team is responsible for ensuring the safe and effective deployment of OpenAI technologies across developers and enterprises. We act as trusted technical partners, helping customers move from experimentation to production by designing, implementing, and scaling real-world AI applications. The Codex Deployment Engineering team focuses on enabling organizations to adopt next-generation AI coding tools and intelligent automations throughout their software development lifecycle. We partner directly with engineering teams to integrate Codex into their workflows — from early experimentation and pilot design through enterprise-scale production rollout — ensuring AI-enhanced developer experiences are reliable, secure, and deeply embedded within customer environments. ### **About the role** We are seeking an experienced technical leader to manage a team of AI Deployment Engineers responsible for driving successful Codex adoption across strategic customers. In this role, you will lead engineers who work hands-on with customer development teams to design AI-enabled workflows, deploy production-ready solutions, and establish scalable patterns for AI-powered software development. As a manager, you will define how deployment engagements operate at scale — setting technical strategy, coaching engineers, and ensuring consistent execution across customer implementations. You will serve as both a people leader and technical advisor, partnering closely with Sales, Product, Research, and Engineering teams to translate customer needs into deployment best practices and product insights. Success in this role will be measured by production deployments, sustained developer adoption, and the creation of repeatable deployment patterns that accelerate Codex usage across organizations. This role is open in both our London and Munich office. We use a hybrid work model of 3 days in the office per week and offer relocation assistance to new employees. ### **In this role, you will:** * Lead, hire, and mentor a high-performing team of AI Deployment Engineers supporting Codex customers across strategic accounts. * Own the operating model and engagement strategy for Codex deployment efforts, ensuring customers successfully move from pilot to production adoption. * Guide teams in designing and implementing AI-enhanced development workflows, automations, and scalable deployment architectures. * Act as the senior technical escalation point for complex customer implementations and deployment challenges. * Partner with Sales, Product, Research, and Applied Engineering teams to align customer outcomes with product direction and roadmap priorities. * Help establish repeatable deployment playbooks, technical patterns, and best practices that enable scaled adoption of AI coding tools. * Coach engineers to operate as trusted advisors to engineering leadership and executive stakeholders. * Synthesize insights from customer deployments and translate them into actionable feedback for internal teams. * Champion safe, reliable, and effective adoption of AI-powered development workflows across industries. ### **You might thrive in this role if you:** * Have 8+ years of experience in technical customer-facing roles such as deployment engineering, solutions architecture, technical consulting, or post-sales engineering. * Have 2+ years of experience leading technical teams, including hiring, mentoring, and developing engineers. * Have experience deploying Generative AI, developer platforms, or cloud-based software solutions into production environments. * Possess hands-on technical experience with software development systems and programming languages such as Python or JavaScript. * Understand modern sof