AVP AI Governance Artificial Intelligence MIT

Lead Mashreq’s enterprise-wide AI Governance program to ensure AI and ML (including GenAI/LLMs) are responsible, compliant, secure, fair, explainable, and well-controlled across their lifecycle. Establish policies, standards, and controls; oversee model risk governance; and enable safe, value-creating AI adoption aligned to Mashreq’s strategy, regulatory expectations, and customer trust.

• AI Policy & Standards
• Define, publish, and maintain Mashreq’s AI Governance Policy, standards, and procedures (Responsible AI, model lifecycle, GenAI safety, human-in-the-loop, data & privacy, monitoring).
• Embed policy into SDLC/MLOps, change management, and risk frameworks.
• GenAI / LLM Controls
• Define guardrails for prompt security, data leakage prevention, content safety, output evaluation, and usage logging.
• Regulatory & Assurance
• Interpret applicable regulations and guidance; evidence compliance and audit readiness.
• Risk Management & Security Integration
• Align AI controls with Cybersecurity, Data Protection, Operational Risk, and Third‑Party Risk.
• Implement access controls, encryption, privacy-by-design, and incident response for AI systems.
• Governance Operating Model
• Design RACI and governance workflows, from use‑case intake to go‑live and sunset.
• Drive adoption of tools (model registry, monitoring dashboards, policy attestations).
• Stakeholder Enablement & Culture
• Train teams on Responsible AI; run awareness campaigns; publish guidance/playbooks.
• Partner with Business, Technology, Data, Risk, Compliance, Legal, and Audit to enable safe innovation.
• Metrics & Reporting
• Define KPIs/KRIs (policy adherence, coverage, validation backlog, incidents, bias and drift metrics).
• Provide executive dashboards and regular reporting to leadership committees.
• Portfolio Oversight & Prioritization
• Triage and prioritize AI use cases; ensure value vs. risk trade-offs and timely approvals.
• Escalate material risks and recommend risk treatment or go/no‑go decisions.
• Continuous Improvement
• Benchmark against leading frameworks (e.g., risk management, AI RMF, ISO standards).
• Industrialize governance processes and automate controls.
  

 Operates within Mashreq policies, risk appetite, IT standards, data protection requirements, and applicable regulatory guidance.

 Works cross‑functionally with Technology (AI/ML Engineering, Data Platform, Cybersecurity), Risk, Compliance, Legal, Audit, and Business Units; engages external vendors/partners under third‑party risk controls.

 Boundaries include approval mandates defined by Risk Committees, budget authority, and change governance.

Knowledge & Experience

 Risk & Compliance: Familiar with model risk management concepts, Responsible AI principles, and audit practices.

 Leadership & Communication: Executive stakeholder management, committee engagement, policy writing, training and change management.

 Education & Certifications: Bachelor’s/Master’s in Computer Science, Data Science, Engineering, or related. Relevant certifications in risk, audit, or AI governance are advantageous.

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