AI Enablement Program Manager

• Lead the end-to-end delivery of multiple AI, ML, and GenAI initiatives across global business functions.
  
• Develop program roadmaps, delivery plans, milestones, resource plans, budgets, and success metrics aligned with business priorities.
  
• Coordinate cross-functional teams spanning AI engineering, data science, product, data engineering, MLOps, IT, security, and business operations.
  
• Drive AI use-case identification, prioritization, proof-of-concept delivery, production deployment, and enterprise-scale adoption.
  
• Manage program risks, dependencies, issues, and stakeholder communications while ensuring timely delivery and measurable business outcomes.
  
• Oversee production readiness, operational handover, performance monitoring, and continuous improvement of AI solutions.
  

• Lead and coordinate data governance and data cataloging workstreams to support enterprise AI readiness.
  
• Partner with data owners, data stewards, data architects, and governance teams to establish data ownership, stewardship, metadata standards, and governance processes.
  
• Drive implementation and adoption of enterprise data catalog and governance platforms, including capabilities for business glossaries, metadata management, data lineage, data classification, and governance workflows.
  
• Coordinate platform configuration, integration with enterprise data sources, requirements gathering, testing, deployment, and business adoption.
  
• Support the implementation and operationalization of platforms such as Collibra, or equivalent data governance solutions.
  
• Ensure AI initiatives leverage trusted, discoverable, high-quality, and appropriately governed data assets.
  
• Establish governance processes for data access, sensitive data handling, data quality, and compliance with enterprise security policies.
  

• Collaborate with cybersecurity, privacy, legal, risk, and compliance teams to ensure AI solutions meet enterprise governance and regulatory requirements.
  
• Support responsible AI practices, including risk assessments, data privacy, access controls, auditability, and appropriate human oversight.
  
• Coordinate with MLOps and engineering teams on model deployment, monitoring, lifecycle management, and production support.
  
• Ensure AI solutions and underlying data assets meet agreed standards for scalability, reliability, security, and operational readiness.
  

• Engage senior business and technology stakeholders to align AI initiatives with strategic objectives.
  
• Establish program governance, executive reporting, delivery KPIs, and escalation mechanisms.
  
• Track business benefits, AI adoption, productivity improvements, and return on investment.
  
• Drive organizational change, stakeholder engagement, and adoption of AI solutions and data governance practices across global teams.
  
  

Requirements

• 10+ years of experience in technology program management, enterprise transformation, AI/ML delivery, data management, or related fields.
  
• Experience with Data Intelligence, Cataloging, and Governance.
  
• Demonstrated experience managing complex, cross-functional technology programs, preferably involving enterprise AI/ML or GenAI implementations.
  
• Strong understanding of the AI lifecycle, including use-case discovery, development, deployment, production and ongoing monitoring.
  
• Experience in data governance, data cataloging, metadata management, data quality, data lineage, or enterprise data management.
  
• Experience coordinating enterprise platform implementations, system integrations, and business adoption initiatives.
  
• Strong program governance, stakeholder management, risk management, planning, and executive communication skills.
  
• Familiarity with cloud-based data and AI ecosystems and enterprise security requirements.
  

• Experience with Collibra implementation, configuration, integration, or adoption (experience with comparable platforms such as Alation, Informatica, and/or Microsoft Purview is preferred).
  
• Understanding of business glossaries, data stewardship, metadata harvesting, data lineage, and governance operating models.
  
• Experience delivering GenAI, LLM-based applications, predictive analytics, or AI-enabled business processes.
  
• Familiarity with MLOps, model monitoring, CI/CD, responsible AI, and AI governance frameworks.
  
• PMP, PgMP, Agile, cloud, or data governance certifications are an advantage.