The Role
Leads enterprise AI, ML, and GenAI programs from ideation through production, coordinating engineering, data science, MLOps, product, security, and business teams. Owns roadmaps, governance, delivery, risk, stakeholder communication, value realization, and operational readiness. Also manages data governance and cataloging initiatives involving metadata, lineage, stewardship, data quality, Collibra or comparable platforms, responsible AI, privacy, and compliance.
Summary Generated by Built In
Our client, a leading global Healthcare organization, is seeking an experienced AI Enablement 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 hands-on experience delivering AI, Data Governance, Data Cataloging (Purview/ Collibra), 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 for 1 year with the likelihood of extension based upon the Client's needs.
The Role:
1. AI Program Management & Enablement
- 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.
2. Data Governance, Cataloging & Collibra Enablement
- 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.
3. AI Governance, Security & Operational Readiness
- 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.
4. Stakeholder Management & Value Realization
- 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.
Preferred Qualifications
- 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.
Skills Required
- 10+ years of experience in technology program management, enterprise transformation, AI/ML delivery, data management, or related fields
- Experience with data intelligence, data cataloging, and data governance
- 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 or comparable platforms such as Alation, Informatica, or Microsoft Purview
- 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
Am I A Good Fit?
Get Personalized Job Insights.
Our AI-powered fit analysis compares your resume with a job listing so you know if your skills & experience align.
Success! Refresh the page to see how your skills align with this role.
The Company
What We Do
Meta Resources Group helps businesses execute complex business and technology initiatives by providing expert delivery teams, solutions architecture, IT staffing, and training, offering cutting-edge digital solutions.
.jpeg)
