VP, AI Audit – Shared Services
Posted 3hrs ago
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Job Description
VP leading AI and GenAI audits for a bank’s governance, risk, and compliance. Assessing model risk, cybersecurity, regulations, and third-party AI platforms while developing audit teams.
Responsibilities:
- Develop and implement risk-based AI/GenAI audit strategies aligned with the Bank's AI agenda and regulatory expectations
- Execute audits across the AI/ML lifecycle, including data sourcing, training, validation, deployment, monitoring, retraining, and decommissioning
- Provide assurance on AI governance, model risk management, ethics, fairness, bias, explainability, and human-in-the-loop controls
- Audit GenAI/LLM use cases, including RAG pipelines, fine-tuning, prompt engineering, guardrails, vector databases, and output validation
- Assess AI cybersecurity risks such as adversarial attacks, prompt injection, data poisoning, model theft, and jailbreaks
- Evaluate third-party AI risks involving foundation model providers and cloud AI platforms
- Assess compliance with AI and data regulations including CBUAE, QCB, SBP, RBI, and UAE PDPL
- Audit AI use in credit, AML/fraud, KYC, chatbots, personalization, trading, and operations automation
- Prepare and present audit reports to the Board Audit Committee, GCEO, and senior management
- Support Internal Audit AI transformation through continuous auditing, GenAI-enabled audit tools, and audit team upskilling
- Guide, coach, and develop AI audit team members
- Support integrated audits with AI and technology subject-matter expertise across the Bank
Requirements:
- Bachelor's degree in Computer Science, IT, Data Science, AI, Statistics, Mathematics, or a related quantitative field
- Minimum 10–12 years in IT audit, technology risk, model risk, or AI/data governance
- At least 3–4 years directly focused on AI/ML or GenAI risk, governance, or audit
- Banking experience preferred
- CISA mandatory or to be obtained within 12 months
- Strong understanding of supervised, unsupervised, reinforcement, and deep learning, NLP, and computer vision
- Knowledge of foundation models, transformers, embeddings, RAG, fine-tuning, prompt engineering, agentic AI, and multimodal AI
- Familiarity with OpenAI, Anthropic, Google, Meta, Mistral, and open-source models
- Experience with Azure OpenAI, AWS Bedrock/SageMaker, Google Vertex AI, Databricks, Hugging Face, LangChain, and vector databases
- Knowledge of AI governance and risk frameworks
- Strong analytical and problem-solving skills focused on novel AI risks
- Excellent communication and interpersonal skills for technical and non-technical stakeholders, including the Board
- Ability to work independently, lead a team, and collaborate across departments and geographies

















