Manager, Applied AI Engineering (Codex)

Quick Facts

• Role: Manager, Applied AI Engineering (Codex)

Description

Lead a team of Applied AI Engineers to drive successful Codex adoption across strategic customers, designing and building AI-enabled development workflows. You will own the technical engagement strategy and operating model to take customers from initial exploration to meaningful, scaled deployment. You will also partner with Sales, Product, Research, and Engineering to create repeatable technical patterns and product insights.

Responsibilities

• Lead, hire, and mentor Applied AI Engineers supporting Codex customers across strategic accounts
• Own the operating model and technical engagement strategy for Codex adoption
• Guide design and implementation of AI-enhanced development workflows, agentic systems, automations, evaluations, and scalable architectures
• Serve as senior technical escalation point for complex customer implementations
• Partner cross-functionally with Sales, Product, Research, and Engineering to align outcomes with product direction
• Establish repeatable patterns, playbooks, reference architectures, and best practices
• Coach engineers to operate as trusted technical partners to customer engineering leaders and executives
• Synthesize customer learnings into actionable feedback for Product/Research/Engineering
• Develop deep understanding of how customers use Codex and where friction occurs
• Champion safe, reliable, and effective adoption of AI-powered development workflows

Requirements

• 8+ years of experience in deeply technical, customer-facing roles (applied engineering, solutions architecture, deployment engineering, technical consulting, or similar)
• 2+ years of experience leading technical teams (hiring, mentoring, developing engineers)
• Experience building or deploying generative AI, developer platforms, agentic systems, or cloud-based software solutions in production
• Hands-on software engineering experience with fluency in Python or JavaScript
• Strong intuition for modern software development lifecycles and how AI/coding agents affect design, build, test, and maintenance
• Ability to work directly with customer engineering teams to tackle ambiguous problems and deliver working solutions
• Strong communication skills across engineering and executive stakeholders
• Ability to thrive in ambiguous, fast-moving environments while building new operating models and technical patterns
• Demonstrated ownership, humility, technical judgment, and commitment to helping customers and teammates succeed
• Commitment to safe and beneficial development of AI

Benefits

• Hybrid work model (3 days in the office per week)
• Relocation assistance for new employees (where applicable)