AVP, AI Program Manager.Artificial Intelligence.MIT
At a Glance
- Category
- 🏦 Finance & Banking
- Level
- C-Level
- Type
- Full-time
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Job Purpose
Lead and govern the bank-wide portfolio of Artificial Intelligence programs, ensuring alignment with strategic objectives, regulatory expectations, and enterprise risk frameworks.
The role is accountable for end-to-end program delivery across AI initiatives, including prioritization, execution oversight, value realization, and governance, while ensuring responsible AI adoption at scale.
Key Result Areas
- AI Program Governance & Delivery
- Establish and manage centralized governance for all AI programs
- Ensure structured lifecycle management from ideation to deployment and scaling
- Portfolio Prioritization & Resource Optimization
- Drive prioritization aligned with business value, regulatory requirements, and resource constraints
- Optimize utilization of AI infrastructure (e.g. GPU, platforms) and delivery capacity
- Execution Oversight
- Track progress, risks, dependencies, and ensure timely delivery of AI initiatives
- Implement standardized program management frameworks and reporting
- Value Realization
- Define and monitor KPIs linked to business outcomes (revenue, cost, risk reduction, efficiency)
- Ensure measurable and auditable value realization
- AI Governance & Compliance
- Ensure all programs comply with internal governance, Model Risk, and regulatory (e.g. CBUAE) guidelines
- Embed responsible AI principles (fairness, explainability, security, auditability)
- Stakeholder Management
- Engage with senior stakeholders across business, risk, compliance, and technology
- Provide executive-level reporting (SteerCo, GCEO updates)
- Vendor & Partner Management
- Oversee delivery partners, vendors, and strategic collaborations
- Ensure alignment with contractual, delivery, and quality expectations
Decision Making Authority & Responsibility
- Accountable for AI program portfolio governance and delivery outcomes
- Recommends prioritization, funding allocation, and execution strategies
- Escalates critical risks and trade-offs to senior leadership as required
- Approves program-level frameworks, reporting standards, and governance controls
Knowledge, Skills and Experience
• Education:
Bachelor’s degree in Computer Science, Engineering, or related field; Master’s preferred
• Experience:
• 12–15+ years of experience in technology program management, with strong exposure to AI/ML initiatives
• Proven track record managing large-scale, cross-functional transformation programs
• Experience in banking or financial services preferred
• Skills:
• Strong program management and portfolio governance expertise
• Understanding of AI/ML lifecycle, data platforms, and enterprise architecture
• Knowledge of regulatory and risk frameworks applicable to AI
• Stakeholder management at executive level
• Strong analytical, communication, and decision-making skills
Requirements
- •Bachelor’s degree in Computer Science, Engineering, or related field
- •Master’s degree preferred
- •12–15+ years of experience in technology program management
- •Strong exposure to AI/ML initiatives
- •Proven track record managing large-scale, cross-functional transformation programs
- •Experience in banking or financial services preferred
- •Strong program management and portfolio governance expertise
- •Understanding of AI/ML lifecycle, data platforms, and enterprise architecture
Responsibilities
- •Establish and manage centralized governance for all AI programs
- •Ensure structured lifecycle management from ideation to deployment and scaling
- •Drive prioritization aligned with business value and regulatory requirements
- •Optimize utilization of AI infrastructure (e.g. GPU, platforms)
- •Track progress, risks, dependencies, and ensure timely delivery
- •Define and monitor KPIs linked to business outcomes (revenue, cost, risk reduction)
- •Ensure compliance with internal governance, Model Risk, and regulatory guidelines
- •Engage with senior stakeholders and provide executive-level reporting
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