AI Specialist

AI Specialist - Group Internal Audit Background:

Group Internal Audit is executing a strategic roadmap to scale our data-enabled and AI-powered internal audit function. Our objective is to improve audit quality, risk coverage, productivity, and stakeholder value through the responsible use of AI. The strategy focuses on embedding AI into core audit processes and decision-making rather than isolated use cases. This includes enhancing our technology stack, capabilities, data and development of guardrails to ensure responsible use of AI and outcomes used for assurance.

Priority initiatives include Dynamic Risk Assessment, AI-enabled and intelligent quality assurance review, pre-planning, planning, fieldwork and reporting. As part of the strategy, GIA is establishing a secure enterprise AI environment on Azure AI Foundry integrated with Microsoft Fabric and the broader data ecosystem. Copilot, Copilot Studio and Copilot Git Hub is currently in use. GIA is seeking specialist AI expertise to support our current team to accelerate implementation and scale high-value use cases.

Required capabilities include enterprise AI architecture, GenAI, machine learning, data engineering, MLOps, AI governance, and change enablement.

• AI/GenAI solution design;
• agentic AI workflow design;
• prompt engineering;
• data engineering and data quality assessment;
• analytics and risk scoring;
• Python/SQL and API integration;
• Microsoft Azure/Fabric or equivalent enterprise data platform experience;
• Copilot, Copilot Studio and Copilot Git Hub
• Power BI or dashboard/reporting design;
• secure software delivery;
• Responsible AI,
• model risk management,
• privacy and information security controls;
• internal audit/risk management domain understanding;
• requirements facilitation;
• UAT coordination;
• documentation,
• training and stakeholder management.

• Senior AI/GenAI delivery resource with 5+ years in analytics/AI solution delivery and at least 2+ years hands-on GenAI/LLM or agentic AI delivery.
• Demonstrated experience delivering AI solutions in a regulated financial services or banking environment, including secure data handling, model governance, testing and business adoption.
• Prior internal audit, risk assessment, assurance automation or control-testing experience is strongly preferred.
• Must be able to work independently with business, data, risk, technology and governance stakeholders and produce high-quality RFQ, design, test and handover documentation.