Sr. Manager, Enterprise AI Programs

Primary Function of the Position

We are seeking a hands-on Sr. Manager to lead Intuitive's AI Code Assistant Platform and AI Enterprise Tools programs: governed, self-service access to AI coding tools, models, and internal data for engineers, and phased company-wide deployment of enterprise AI tools for all business teams. The ideal candidate has a strong technical program management background in developer platforms or AI/ML enablement, experience coordinating engineering, security, and learning & development teams, and solid knowledge of AI assistants, data-access patterns, and identity and access governance. You will build and grow a team as needed to support the growth of these tools. This is a self-starter who takes ownership, clears roadblocks without waiting for direction, and gets work done. You will turn an approved roadmap into delivered capability, manage budget and timelines, and report progress and ROI to executives, influencing across teams without direct authority. This role reports to the owner of both programs.

Essential Job Duties

• Own and maintain the multi-year project plan across all workstreams of the AI Code Assistant Platform and AI Enterprise Tools rollout, driving delivery against committed milestones, budget, and owners.
• Serve as the single point of accountability for both programs, resolving cross-team blockers and escalating decisions that need executive input.
• Partner with Security and IT Architecture to govern how engineers, employees, and autonomous agents access company tools and data (including enterprise AI tool integrations), including authentication, access provisioning, and risk management.
• Coordinate the build of a unified, governed interface spanning multiple AI coding tools, models, and vendors, including usage governance across the platform.
• Lead the phased AI Enterprise Tools rollout, from pilot through company-wide deployment: coordinate IT, Security, Legal, HR, and business-unit leaders on admin configuration, SSO and provisioning, use-case onboarding, data-handling policy, and change management.
• Drive modernization of internal tools and systems so they work well with AI assistants, and guide evaluation of emerging model options.
• Own the training curriculum and enablement roadmap, including required training, ongoing learning content, and a recurring lunch-and-learn series, for both engineers and business users.
• Build and manage a champions network that drives adoption and provides frontline support across engineering and business functions.
• Track and report program success metrics, maintaining a leadership-facing dashboard that demonstrates adoption and return on investment across both programs.
• Over time build, lead, and grow a team of specialists, scaling headcount as tool adoption and scope expand, while remaining hands-on in delivery.

Required Skills and Experience

• 10+ years in technical program/product management, including 3+ years building and managing teams and leading a platform, developer-tools, or AI/ML enablement program at enterprise scale.
• Demonstrated ability to run cross-functional programs spanning engineering, security, and learning & development, with budget and executive-reporting ownership.
• Working knowledge of developer tooling and AI coding assistants (e.g., Claude Code, Devin, Copilot, Cursor) and enterprise AI productivity tools and how engineering teams adopt them.
• Understanding of how AI tools integrate with internal systems and data sources.
• Effectively communicate technical concepts to non-technical audiences to foster understanding, influence, and build consensus across teams.
• A proven self-starter who drives work to completion, removes roadblocks independently, and manages and influences without direct authority.
• Strong written and verbal communication; comfortable presenting to engineering leadership and cross-functional steering committees.

Required Education and Training

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering Management, or a related field.

Preferred Skills and Experience

• Experience establishing governance for autonomous or agentic AI systems.
• Experience building an internal champions or community-of-practice program at a similar scale.
• Background in regulated or compliance-sensitive environments, such as medical device or financial services.
• Experience evaluating or deploying AI model options, including open-source or self-hosted models.