AI Governance, Lead Product Manager

UPS

1d•Hybrid

About The Position

The Lead Product Manager of AI Governance defines the strategy, roadmap, and platform vision for how UPS governs AI, GenAI, and intelligent agents at scale —and for the platforms and automation that make it possible. This role owns the direction: the multi-year roadmap for governance capabilities, the evolution of the operating model, and the executive relationships that keep governance aligned to enterprise priorities. Working across Legal, Privacy, Security, Compliance, Enterprise Architecture, and business and IT teams, the Lead decides where to invest in governance platforms, workflow automation, and lifecycle tooling to move from manual oversight to governance that scales. This role serves as the enterprise owner for AI governance platforms and automation —delivered through IBM watsonx.governance and the broader governance toolset.

Requirements

Bachelor's degree in Information Systems, Computer Science, Business, Engineering, Data Analytics, or a related field.
3 to 5 years of experience in AI/data governance, risk, product management for platforms and tooling, or technology strategy.
Experience leading enterprise governance programs, platform initiatives, or automation efforts.
Demonstrated experience setting strategy and roadmaps and influencing senior business and technical stakeholders.
Strong understanding of AI, machine learning, and the AI lifecycle.

Nice To Haves

Direct experience building or scaling governance platforms and automation (IBM watsonx.governance or equivalent).
Working knowledge of AI Governance frameworks (NIST AI RMF, ISO/IEC 42001, and the EU AI Act).
Expertise in Agile and product/platform lifecycle management.
Professional certifications such as IAPP AIGP, CIPP, or equivalent.
Prior experience mentoring or leading teams in a governance or regulated environment.

Responsibilities

Lead the AI governance strategy, roadmap, and KPIs, and set investment priorities for governance platforms, automation, and tooling.
Drive the evolution of the governance operating model—how governance runs at scale and where automation replaces manual work.
Set the direction for platform capabilities across the AI lifecycle—intake, risk assessment, monitoring, drift, incident response, change control, and retirement—delivered through watsonx.governance and integrated tooling.
Define the target-state workflows and automation that embed governance into how AI is built and deployed.
Anticipate emerging AI risk and regulation (NIST AI RMF, ISO/IEC 42001, EU AI Act) and shape the roadmap to stay ahead of it.
Govern the lifecycle model for AI agents, reusable assets, prompts, models, and inventories.
Mentor Senior Product Managers and cross-functional contributors, elevating governance platform and product maturity across the organization.