The Enterprise Application & Engineering team within KPMG Information Technology Services is dedicated to creating and delivering value to our business by leveraging on IT technology. The team is responsible for delivering customer-focused solutions and high-quality IT services internally to enable our business.
Job Description
1. Software Development Strategy & Architecture Leadership
- Lead and shape the software engineering vision for Enterprise Applications, aligning long‑term strategic objectives with enterprise architecture, business priorities, and evolving data protection, cyber security, and internal compliance requirements.
- Proactively assess the impact of emerging technologies, including Generative AI, on the organisation's software architecture, development practices, and operating models.
- Define and sustain enterprise-wide software engineering strategies, standards, and governance to support cloud site reliability, resilience, and stable operations.
2. Software Engineering Oversight & Delivery Excellence
- Provide overall leadership to Tech Leads and developers, establish governance for software design, development, integration, and deployment across EA&E.
- Drive the adoption of modern and scalable software engineering methodologies, leveraging Azure Cloud Stack, platform engineering, and AI‑enabled development practices.
- Drive innovation by evaluating and introducing novel approaches in software design, development, and delivery, including AI‑augmented development and automation.
- Assess the feasibility, risks, and value of proposed changes to development methodologies, tools, and technical standards prior to enterprise-wide adoption.
- Ability to provide technical guidance to embed cloud security principles, reliability, fault‑tolerance, and performance considerations into software engineering standards and delivery practices.
Knowledge, Expertise & Abilities – Generative AI Focus
The role requires a strong foundation in Generative AI concepts and their practical application within software engineering:
- Knowledge of Generative AI model architectures and workings, including training data, algorithms, pipelines, and output generation.
- Hands-on experience building applications around generative AI models.
- Ability to apply Generative AI concepts to real-world enterprise use cases, such as summarisation, reasoning, inference, content transformation, and augmentation.
- Experience evaluating Generative AI model performance, including analysis of metrics, limitations, and sensitivity to prompt variations.
- Ability to guide teams in the responsible adoption of Generative AI within software development lifecycles, tooling, and delivery processes.
The ideal candidate should:
- Possess a Bachelor's degree in Computer Science, Information Technology, or related field
- A minimum of 10 years of progressive technical experience in enterprise application development, with strong expertise in the Azure Cloud stack.
- Proven experience in leading engineering teams and developing enterprise‑scale software engineering solutions on the Microsoft Azure Cloud platform, including PaaS and cloud‑native architectures.
- Strong proficiency in modern application development using Microsoft technologies (e.g. .NET, .NET Core, Web APIs, cloud‑native architectures) and deep expertise in full stack development including but not limited to ReactJS and NodeJS.
- Strong hands‑on and understanding of core Azure services, such as Azure App Service, Azure Functions, Azure API Management, Azure Kubernetes Service (AKS), Azure SQL / Cosmos DB, Azure Storage, Azure Key Vault, and Azure Active Directory.
- Knowledge of Azure reliability and monitoring capabilities (e.g. Azure Monitor, Application Insights, Log Analytics, Azure Advisor) to support operational stability and proactive incident prevention.
- Excellent verbal/written communication, collaboration, analytical and presentation skills
- Microsoft Azure Certifications are mandatory
