AVP, AI Program Manager.Artificial Intelligence.MIT
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Key skills for this role
About the Role
Lead and govern the bank-wide portfolio of Artificial Intelligence programs, ensuring alignment with strategic objectives, regulatory expectations, and enterprise risk frameworks.
Key Skills for This Role
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, regulatory requirements, and resource constraints
- Optimize utilization of AI infrastructure (e.g. GPU, platforms) and delivery capacity
- Track progress, risks, dependencies, and ensure timely delivery of AI initiatives
- Implement standardized program management frameworks and reporting
- Define and monitor KPIs linked to business outcomes (revenue, cost, risk reduction, efficiency)
- Ensure measurable and auditable value realization
- Ensure all programs comply with internal governance, Model Risk, and regulatory (e.g. CBUAE) guidelines
- Embed responsible AI principles (fairness, explainability, security, auditability)
- Engage with senior stakeholders across business, risk, compliance, and technology
- Provide executive level reporting (SteerCo, GCEO updates)
Requirements
- Bachelor's degree in Computer Science, Engineering, or related field; Master's preferred
- 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
- 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
Full Job Posting
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
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