Responsibilities

• Lead the end-to-end delivery of multiple AI, Machine Learning, and Generative AI programs across global business functions.
  
• Drive AI initiatives from business intake through planning, delivery, deployment, production, and value realization.
  
• Partner with Product Owners, AI Engineers, Data Scientists, MLOps teams, and business stakeholders to deliver scalable AI solutions.
  
• Manage AI delivery roadmaps, dependencies, milestones, budgets, risks, and executive reporting across multiple concurrent initiatives.
  
• Coordinate cross-functional teams spanning Business, Data Engineering, AI Engineering, Platform, Security, Governance, and Change Management.
  
• Operate within Agile delivery methodologies including Scrum, SAFe, Kanban, and hybrid delivery models tailored for AI development.
  
• Facilitate Agile ceremonies including Sprint Planning, Backlog Grooming, PI Planning, Reviews, Retrospectives, and Release Planning.
  
• Manage AI-specific delivery backlogs including data readiness, feature engineering, model training, model validation, deployment readiness, and Responsible AI reviews.
  
• Work within an enterprise AI Factory operating model, ensuring reusable assets, accelerators, governance frameworks, and shared AI platforms are leveraged effectively.
  
• Drive AI Factory intake, prioritization, capacity planning, governance, and delivery throughput across multiple business initiatives.
  
• Lead Value Teams focused on measurable business outcomes rather than traditional project milestones.
  
• Champion Value-Based Delivery by aligning delivery priorities with defined business KPIs, measurable value hypotheses, ROI, and operational outcomes.
  
• Monitor AI program health using delivery metrics including model cycle time, deployment velocity, adoption, business value realization, and delivery performance.
  
• Manage AI delivery risks including data quality, model performance, governance, Responsible AI, regulatory compliance, and organizational readiness.
  
• Support enterprise governance forums, AI steering committees, executive portfolio reviews, and business leadership reporting.
  
• Coordinate User Acceptance Testing (UAT), production readiness, deployment planning, hypercare, and post-production stabilization.
  
• Ensure AI initiatives comply with enterprise architecture standards, data governance policies, security requirements, and Responsible AI frameworks.
  
• Build strong relationships with executive stakeholders while translating complex AI delivery concepts into business-focused outcomes.
  
• Mentor delivery teams on Agile best practices specifically adapted to AI and Data Product delivery.
  

Requirements

• 8+ years of Program or Project Management experience within enterprise technology organizations.
  
• Minimum 2 years of recent (within the last 24 months) experience delivering AI, Machine Learning, or Generative AI programs.
  
• Demonstrated experience managing enterprise AI delivery from concept through production deployment.
  
• Proven experience delivering AI work products within Agile product delivery environments.
  
• Strong understanding of AI/ML development lifecycle including:
  • Data Readiness
    
  • Feature Engineering
    
  • Model Development
    
  • Model Validation
    
  • Model Deployment
    
  • MLOps
    
  • Model Monitoring
    
  • Responsible AI
    
• Hands-on experience operating within an AI Factory or similar centralized AI delivery model.
  
• Experience leading Value Teams and delivering measurable business outcomes through Value-Based Delivery frameworks.
  
• Strong understanding of Agile methodologies including Scrum, SAFe, Kanban, and Hybrid delivery.
  
• Experience coordinating cross-functional teams including Product, Engineering, AI, Data Science, Security, Business, and Governance functions.
  
• Experience managing enterprise portfolios, risks, dependencies, executive reporting, and delivery governance.
  
• Strong stakeholder management and executive communication skills.
  
• Experience supporting enterprise AI governance, Responsible AI practices, and compliance initiatives.
  
• Ability to manage multiple concurrent AI programs within fast-paced enterprise environments.
  
• Bachelor's degree in Computer Science, Engineering, Information Systems, Business, Data Science, or a related discipline.
  

Preferred Qualifications

• Healthcare, Pharma, or Life Sciences industry experience.
  
• Experience delivering Generative AI (GenAI) initiatives.
  
• Experience with Collibra data catalog is a Big Plus
  
• Familiarity with Azure AI, Azure OpenAI, AWS SageMaker, Google Vertex AI, or similar enterprise AI platforms.
  
• Experience with MLOps platforms and AI deployment pipelines.
  
• Exposure to Data Mesh, Modern Data Platforms, or AI Platform Engineering.
  
• PMP, SAFe, Scrum Master, Agile, or Product Management certifications.
  
• Experience working with Responsible AI frameworks and AI governance boards.
  
• Executive stakeholder engagement within global transformation programmes.