VP-AI Audit.Shared services_Audit

Mashreq

IndiaremotePosted 2 days ago

Skill Required

AI-Audit-DirectorVP-Internal-AuditAI-Governance-ManagerAI-Risk-ManagerRegulatory-Compliance-ManagerAI-AuditAI-AuditingAI-AuditorArtificial-Intelligence-AuditorAuditAIGenerative AIComputer VisionDeep LearningCybersecurityLangChainEngineeringStatisticsDatabricksanalyticalautomationObservabilityanalyticsMLflowOpenAPIAzureOWASPCloudMachine LearningNLPRAGAWSandFulltime

Key highlights

Requires CISA certification (mandatory or obtainable within 12 months)
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
Preferably in banking/financial services
Master's in AI/ML or Data Science preferred
Preferred additional certifications include ISACA AAIA, CISSP, CRISC, CGEIT, CDPSE

Role overview

This role serves as an AI/GenAI audit specialist within a bank's Internal Audit function, responsible for developing and executing risk-based audit strategies across the full AI/ML lifecycle. The position combines deep technical AI expertise with audit and governance competencies, requiring the incumbent to provide assurance on AI systems, assess emerging risks, ensure regulatory compliance, and guide the internal audit team's transformation through AI-enabled tools and methodologies.

Responsibilities

Develop and implement risk-based AI/GenAI audit strategies aligned with the Bank's AI agenda and regulatory expectations.
Execute audits over the AI/ML lifecycle — data sourcing, training, validation, deployment, monitoring, retraining, and decommissioning (MLOps/LLMOps).
Provide assurance on AI governance, model risk management (MRM), ethics, fairness, bias, explainability, and human-in-the-loop controls.
Audit GenAI/LLM use cases — RAG pipelines, fine-tuning, prompt engineering, guardrails, vector databases, and output validation.
Assess AI cybersecurity risks — adversarial attacks, prompt injection, data poisoning, model theft, jailbreaks (OWASP LLM Top 10, MITRE ATLAS).
Evaluate third-party AI risks covering foundation model providers (OpenAI, Anthropic, Google, Meta, Mistral, open-source) and cloud AI platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI).
Assess compliance with AI and data regulations — CBUAE, QCB, SBP, RBI, UAE PDPL etc.
Audit AI use in credit, AML/fraud, KYC, chatbots, personalization, trading, and operations automation.
Prepare and present impactful audit reports to the Board Audit Committee, GCEO, and senior management, translating complex AI concepts into business language.
Partner in Internal Audit AI transformation — continuous auditing, GenAI-enabled audit tools, and audit team upskilling.
Guide, coach, and develop AI audit team members; foster a culture of learning, agility, and innovation.
Support integrated audits by providing AI/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, with at least 3–4 years directly focused on AI/ML or GenAI risk, governance, or audit, preferably in banking.
CISA mandatory (or to be obtained within 12 months).
Strong understanding of AI/ML concepts — supervised, unsupervised, reinforcement, deep learning, NLP, computer vision.
Deep knowledge of GenAI and LLMs — foundation models, transformers, embeddings, RAG, fine-tuning (SFT, RLHF, LoRA), prompt engineering, agentic and multi-modal AI.
Familiarity with major model versions and providers — OpenAI (GPT-4/4o/5), Anthropic (Claude), Google (Gemini), Meta (Llama), Mistral, and leading open-source models.
Knowledge of AI platforms/tooling — Azure OpenAI, AWS Bedrock/SageMaker, Google Vertex AI, Databricks, Hugging Face, LangChain, vector databases.
Understanding of AI governance and risk frameworks.
Strong analytical and problem-solving skills focused on novel AI risks.
Excellent communication and interpersonal skills to convey complex AI concepts to technical and non-technical stakeholders, including the Board.
Ability to work independently, lead a team, and collaborate across departments and geographies.

Nice to have

Master's in AI/ML or Data Science preferred.
One or more preferred certifications: ISACA AAIA (Advanced in AI Audit), CISSP, CRISC, CGEIT, CDPSE.
Hands-on involvement in any part of an organization's AI initiatives (use case build, model validation, AI governance council, MLOps, GenAI product).
Banking / financial services domain knowledge (credit, fraud/AML, digital channels, compliance).
Experience with AI-enabled internal audit tools and audit analytics.