Director, Data & AI Governance - Flex Location

About the role

We're hiring a Director, Data & AI Governance to lead how UPS scales AI governance, adoption, and organizational change across the enterprise.

Responsibilities

• 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.
• 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.
• 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.
• Track emerging AI and data regulation and translate impact into operating-model and roadmap changes.
• Partner with Legal, Privacy, Compliance, and Security to meet internal and external requirements.
• Align governance controls to NIST AI RMF, ISO/IEC 42001, and the EU AI Act.
• Lead enterprise data governance strategy and operating model, including stewardship, ownership, quality, metadata, lineage, lifecycle, and governance practices that support AI-ready data.
• Report governance maturity and key performance indicators to leadership.
• Build, mentor, and develop a high-performing governance team.
• Set goals, metrics, and development plans; model accountability and continuous improvement.

Qualifications

• Bachelor's degree in Information Systems, Computer Science, Data Analytics, Business, Engineering, Risk Management, or a related field. Master's preferred.
• 10+ years in Data or AI Governance, Information Security, Risk, Information/Data Management, Analytics, or Compliance.
• 7+ years leading teams, programs, and enterprise initiatives.
• Proven record scaling an enterprise governance program and driving adoption and organizational change across a large, federated organization while influencing executive stakeholders.
• Experience designing operating models and implementing automation that improves quality, consistency, and team capacity.
• Direct experience working with executive leadership and governance boards.
• Experience implementing or scaling AI governance platforms such as IBM watsonx.governance or comparable solutions.
• Experience implementing frameworks aligned to NIST AI RMF, ISO/IEC 42001, and emerging AI regulation.
• Track record building executive dashboards and reporting for governance councils, review boards, or Executive Leadership Teams.
• Leadership Skills: Executive communication, Strategic planning, Organizational change management, Cross-functional leadership, Stakeholder management, Program leadership, Decision-making under ambiguity, Coaching & mentoring.
• Technical Skills: Data & AI governance platforms, Data catalog & metadata tools, Analytics & reporting, Cloud (Azure, AWS, GCP), Data architecture concepts, AI/ML concepts and lifecycle management.