Senior Manager–AI Governance and Strategy

Key Responsibilities

• Operate and evolve the AI Control Tower as the central coordination point for enterprise agentic AI initiatives.
• Establish and manage governance frameworks for AI agent intake, prioritization, risk assessment, lifecycle management, and change control.
• Capture and manage the enterprise portfolio of AI agents, including status, dependencies, reuse opportunities, and value realization.

Business Engagement Enablement

• Engage business units, segments, and functions to support AI agent design, development, piloting, testing, and adoption.
• Define training and enablement needs for AI agent deployment.
• Ensure clear business ownership, success metrics, adoption readiness, and ongoing stakeholder alignment.
• Act as the primary interface between business stakeholders and DTIT for agentic AI initiatives.

Data Knowledge Base Strategy

• Lead engagement with business teams on data sourcing strategy for new AI agents.
• Own intake and governance for new product or domain-specific knowledge bases, as well as changes, enhancements, and retirement of existing knowledge bases.
• Coordinate with DTIT on knowledge base setup, seeding, chunking, curation, validation, maintenance, updates, and version control.
• Serve as the business-facing owner for knowledge asset quality, relevance, and fitness for AI use.

Legacy Data Rationalization

• Lead structured efforts to inventory and rationalize legacy unstructured data stores.
• Consolidate content into domain-specific product knowledge bases.
• Eliminate duplication, stale content, and unmanaged repositories.
• Drive standards for content ownership, stewardship, and ongoing governance.

Key Interfaces

• DTIT teams, including architecture, AI platforms, security, data, and change management.
• Business unit and segment leadership.
• Product, sales, services, and operations teams.
• AI platform, knowledge management, and governance functions.

Required Qualifications

• Business degree with MIS or Computer Science background.
• 10+ years of experience in enterprise transformation, digital platforms, data/AI governance, and product operations.
• Strong background in governance, operating models, and portfolio management.
• Demonstrated ability to translate business needs into structured AI, data, and knowledge requirements.
• Prominent track record of managing AI projects through the AI solution lifecycle.
• Strong executive communication and stakeholder management skills.

Preferred Qualifications

• Computer Science, MIS, Business Analytics, or AI/ML certification.
• 3+ years of experience with agentic AI, AI platforms, or AI-enabled workflows.
• Familiarity with knowledge bases, unstructured data management, and content lifecycle governance.
• Familiarity with change management frameworks in large, global organizations.
• Experience rationalizing fragmented data or content ecosystems.