Director, Data & AI Governance - Flex Location

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The Leader We're Looking For A transformation leader who has taken enterprise AI governance from a collection of controls to a scaled, enterprise-wide capability. 10–15+ years across Data, Analytics, Information Security, Risk & Compliance, or AI Governance, with hands-on experience standing up and scaling AI governance programs at enterprise scale.  Equally comfortable shaping the operating model and driving adoption across business units as influencing executive decision-making on AI risk, governance, and adoption.

We're hiring a Director, Data & AI Governance to lead how UPS scales AI governance, adoption, and organizational change across the enterprise. This is a transformation and adoption role first. The role helps scale responsible AI adoption across one of the world's largest logistics and supply chain enterprises. The Director owns the governance operating model and is accountable for evolving existing governance practices into a repeatable, enterprise-wide capability that enables responsible AI adoption at enterprise scale. The Director sets the direction for the operating model, builds the cross-functional coalition needed to make it stick, and drives measurable adoption and business value. The role helps the enterprise accelerate AI adoption by making governance repeatable, scalable, and trusted. Frameworks, policies, and controls matter here—but as means to an end. The real mandate is change: scaling responsible AI practices across a large, federated enterprise and building trust in how we govern data and AI.

Operating Model & Transformation Define the long-term vision and maturity roadmap for enterprise Data & AI Governance. Define and evolve the enterprise AI governance operating model—roles, decision rights, workflows, and the target state for how governance runs at scale. Scale AI governance from a collection of reviews, controls, and processes into an enterprise capability embedded across the AI lifecycle. Drive the adoption of automation and workflow orchestration to improve governance effectiveness and scalability. Lead the adoption and evolution of enterprise AI governance platforms, including IBM watsonx.governance, to support governance, monitoring, and oversight. Set the multi-year roadmap and OKRs for scaling governance across business units, and report progress to executive leadership. Adoption & Organizational Change Drive enterprise adoption of governance practices through change management, communications, education, and executive sponsorship. Partner with business and technology leaders to accelerate AI adoption by embedding governance into delivery and removing barriers while maintaining appropriate governance, risk, and compliance standards. Grow AI fluency and governance awareness across the organization. AI Governance & Responsible AI Define governance approaches for emerging AI capabilities including GenAI, intelligent agents, and reusable enterprise AI assets. Oversee AI use case intake, risk assessment, approval, monitoring, documentation, and lifecycle management at enterprise scale. Establish controls for model governance, explainability, transparency, fairness, accountability, and human oversight. Chair AI Review Boards and executive governance forums and bring the operating model to life through them. Risk, Compliance & Regulatory Track emerging AI and data regulation