Lead end-to-end delivery of enterprise AI/ML/GenAI programs from intake through production and value realization. Coordinate cross-functional teams (Product, AI Engineering, Data Science, MLOps, Security), manage roadmaps, risks, budgets, and governance within Agile/AI Factory operating models. Drive Value-Based Delivery, Responsible AI compliance, deployment readiness, executive reporting, and post-production stabilization while mentoring teams on AI-tailored Agile practices.
This is a remote position.
Our client, a leading global Healthcare and Consulting organization, is seeking an experienced AI Delivery Program Manager to lead enterprise-scale Artificial Intelligence initiatives across global business functions. This is not a traditional Program Management role. The ideal candidate must have recent (within the last two years) hands-on experience delivering AI, Machine Learning, or Generative AI programs, with proven expertise managing AI work products through Agile delivery methodologies, AI Factory operating models, and Value Team delivery frameworks. The successful candidate will partner with business leaders, AI Engineering, Data Science, MLOps, Product, and Enterprise Architecture teams to successfully deliver AI initiatives from ideation through production deployment while ensuring measurable business value and governance throughout the delivery lifecycle.
This is a contractual role which will run through the end of 2026, with likelihood of extension into 2027.
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
- Data Readiness
- 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.
- Healthcare, Pharma, or Life Sciences industry experience.
- Experience delivering Generative AI (GenAI) initiatives.
- 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.
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