Job Purpose
The Internal Audit: Data Enablement Analyst leverages data expertise, digital technologies, and generative AI (GenAI) to support Group Internal Audit's (GIA) Digital Strategy and strategic objectives.
This role delivers fit-for-purpose data and AI-driven products, enhances GIA's data and AI infrastructure, and enables advanced analytics, machine learning, and intelligent automation.
The analyst plays a key role in developing and orchestrating AI agents, deploying solutions via Azure AI Foundry and Microsoft Fabric, and embedding responsible AI practices into audit processes.
Job Responsibilities
Design and implement GenAI and AI-driven solutions to support audit execution, digital assurance, and intelligent automation.
Build, fine-tune, and orchestrate AI agents using frameworks such as Microsoft Agent Framework, LangChain, or Semantic Kernel.
Leverage Azure AI Foundry and Microsoft Fabric to develop, deploy, and manage AI applications and agents within a secure, scalable enterprise environment.
Enhance data and AI infrastructure to support advanced analytics, machine learning, and retrieval-augmented generation (RAG) pipelines.
Implement data pipelines, vector databases, and prompt engineering strategies to support GenAI use cases in internal audit.
Facilitate training and capability building in GenAI tools, prompt engineering, and AI literacy across GIA.
Collaborate with audit teams, data owners, and IT to align on data and AI needs, ensuring secure and ethical use of AI technologies.
Continuously monitor AI model performance, retrain and optimize models, and stay abreast of emerging GenAI trends and tools.
Identify innovation opportunities to improve audit effectiveness through AI and data-driven insights.
Essential Qualification
Relevant Degree/Diploma/Equivalent in Data Science, Computer Science, Information Systems, or related field.
A recognized software development certification/degree/diploma e.g. certification in AI/ML, Data Analytics, or Cloud Platforms (e.g., Azure AI Engineer Associate, Microsoft Certified: Azure Solutions Architect (advantageous).
Minimum Experience Level
2+ years of experience in data analytics, with exposure to AI/ML projects
Familiar with Agile development methodologies
Software development experience is advantageous.
Hands-on experience with GenAI tools, LLMs, or AI agent development preferred
Technical / Professional Knowledge
Generative AI and Large Language Models (e.g., GPT, Claude, Llama)
AI agent orchestration frameworks (e.g., LangChain, Semantic Kernel, Microsoft Agent Framework)
Azure AI Foundry and Microsoft Fabric for AI and data orchestration
Data Science, Data Engineering, and Data Modelling
Retrieval-Augmented Generation (RAG) pipelines and vector databases (e.g., FAISS, Pinecone)
Machine Learning and NLP techniques
Python programming for data processing, AI model development, and automation
SQL and data pipeline development
Microsoft Office
Relevant regulatory knowledge
Relevant software and systems knowledge
Business writing skills
Behavioural Competencies
Applied Learning
Communication
Collaborating
Decision Making
Technical/Professional Knowledge and Skills
Closing date: 26 May 2026