Senior, Full Stack Software Engineer, Financial Accounting Advisory Services

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

EY is the most globally integrated professional services organization which encompasses a separate business unit dedicated exclusively to the financial services marketplace. Join Financial Services (FSO) and you will work with multi-disciplinary teams from around the world to deliver a global market perspective. Aligned to key industry groups including banking and capital markets, wealth and asset management and insurance, we are a leading provider of integrated assurance, advisory, tax, and transaction services dedicated to assisting financial institutions in navigating complex regulatory environments and managing technology risks effectively. We are committed to delivering exceptional service and innovative solutions to our clients. 

The Role

AI is changing how audits are planned, executed, documented, reviewed and evidenced for regulatory scrutiny. We are looking for a hands-on full stack software engineer to design, develop and deploy cloud-based agentic AI solutions that (a) support and enhance audit processes, including regulatory audits for financial services clients, and (b) facilitate the audit of AI systems employed by Financial Institutions.

These solutions may support FEAT review, audit planning, risk assessment, evidence ingestion, document validation, control testing, workpaper generation, issue tracking, quality review and audit workflow automation.

A key part of the role is to develop solutions that facilitate regulatory audits and help clients demonstrate adherence to applicable legal and regulatory requirements, including that of the MAS AI Risk Management Guidelines.

You will work closely with business professionals, auditors, technology risk specialists, regulatory SMEs, data teams and client-facing engagement teams to translate audit and regulatory pain points into practical, secure, auditable and scalable AI solutions. This is a hands-on engineering role for someone who enjoys building — from front-end interfaces and APIs to backend orchestration, Azure services, retrieval-augmented generation and agentic AI workflows.

What You’ll Do

• Develop agentic AI solutions for audit – build AI-powered applications, copilots, workflow agents and automation tools that support audit planning, execution, documentation, review and regulatory audit readiness
• Facilitate regulatory audits – design solutions that help audit teams and clients evidence compliance with legal and regulatory requirements, including MAS AI Risk Management Guidelines, MAS TRM expectations, data protection obligations and internal control standards
• Embed regulatory control requirements into solutions – translate AI governance, model risk, technology risk, data governance, security, privacy and auditability requirements into practical system features, workflows and control checkpoints
• Support AI risk management and governance – enable AI use case inventories, materiality assessments, lifecycle control tracking, human oversight, explainability records, validation evidence, monitoring logs and change management workflows
• Automate audit workflows – design solutions that help audit teams ingest evidence, analyse documents, perform consistency checks, summarise findings and generate draft workpapers or audit outputs
• Build full-stack applications – develop user-friendly front-end interfaces, backend services, APIs, databases and integrations for audit-focused enterprise solutions
• Apply Azure AI technologies – use Azure OpenAI, Azure AI services, Azure Functions, App Services, API Management, Cosmos DB, Azure SQL, Storage, Key Vault and related cloud-native components
• Implement RAG and agentic workflows – create solutions that retrieve, reason over and orchestrate information from audit files, policies, regulatory requirements, client evidence and internal knowledge bases
• Engineer secure, compliant and auditable solutions – apply strong software engineering practices including authentication, access control, encryption, logging, monitoring, testing, CI/CD, data protection and audit trail design
• Partner with audit, risk and regulatory teams – work with subject matter experts to understand audit methodology, evidence standards, regulatory expectations, control testing and quality requirements
• Translate audit and regulatory needs into technology – convert business requirements, regulatory obligations and audit pain points into technical designs, prototypes, MVPs and production-ready solutions
• Support responsible AI adoption – help embed guardrails for human oversight, traceability, explainability, confidentiality, appropriate use and escalation of AI-generated outputs in audit processes

What We’re Looking For

• A degree in a relevant field – Computer Science, Software Engineering, Information Systems, Data Science, Engineering or equivalent practical experience
• 3 to 5 years of experience in full-stack software engineering, cloud application development, AI engineering or technology consulting
• Strong software engineering discipline – clean code, version control, testing, documentation, secure coding, deployment automation and maintainable solution design
• Hands-on full stack development experience with Python, JavaScript, C#, Java and associated full-stack software frameworks
• Practical experience in building enterprise AI solutions based on Agentic AI architecture using LLM Local/Frontier Models
• Backend and API development experience, including REST APIs, microservices, serverless functions or event-driven architectures
• Interest in audit and regulatory innovation – curiosity about how AI can improve audit quality, regulatory audit readiness, evidence review, control testing, documentation, supervision and engagement delivery
• Understanding of AI solution patterns, including prompt design, retrieval-augmented generation, embeddings, workflow orchestration, AI agents or LLM-based applications
• Awareness of risk, compliance and control concepts – familiarity with governance, risk management, control testing, audit trails, data confidentiality, privacy or regulatory reporting is advantageous
• Clear communication skills – able to explain technical concepts to audit, risk, regulatory, business and engineering stakeholders
  
  

Your Credentials — Nice to Have

• Experience with agentic AI frameworks such as Semantic Kernel, LangChain, AutoGen, CrewAI or similar orchestration tools
• Exposure to audit, risk or regulatory technology, including audit workflow tools, GRC platforms, regulatory compliance platforms, control testing automation or document review solutions
• Knowledge of MAS regulatory expectations, including MAS AI Risk Management Guidelines, MAS Technology Risk Management Guidelines, Cyber Hygiene expectations, outsourcing / third-party risk, operational resilience or data governance requirements
• Experience with retrieval-augmented generation, vector databases, embeddings, document intelligence, semantic search or knowledge management solutions
• Microsoft certifications such as Azure Fundamentals, Azure Developer Associate, Azure AI Engineer Associate or Azure Solutions Architect
• Experience with DevOps and infrastructure as code, including Azure DevOps, GitHub Actions, Terraform, Bicep or ARM templates
• Familiarity with containerisation and cloud-native platforms, such as Docker, Kubernetes or Azure Container Apps
• Understanding of financial services audit considerations, including data confidentiality, technology controls, auditability, model governance, regulatory expectations and operational resilience
• Exposure to Responsible AI, AI risk management, privacy, security controls, human-in-the-loop design or technology risk frameworks

Why This Role

• Build the future of audit – develop practical AI solutions that directly support audit teams and improve how audit work is performed
• Support regulatory confidence – create solutions that help clients evidence compliance, respond to regulatory audits and operationalise AI risk management expectations
• Hands-on cloud and AI engineering – gain deep experience across Azure, GenAI, RAG, agentic AI, full-stack development and enterprise integration
• Real impact on audit quality and productivity – create tools that help teams work faster, reduce manual effort and improve consistency of audit documentation and review
• Financial services and assurance specialism – work on technology-enabled audit and regulatory solutions for complex banking and financial services environments
• Career acceleration – develop as both a hands-on engineer and a client-facing audit technology specialist
• Certification and learning support – grow your capabilities in Azure, AI engineering, cloud architecture, audit technology, regulatory technology and responsible AI
• Hybrid working – flexibility to collaborate with teams and clients while maintaining balance