About The Role

The Role

You will be a senior leader, pivotal in driving innovation, accelerating the adoption of cutting-edge technologies, and enhancing our engineering practices. You will specialize in creating robust, scalable, cloud-first architectures leveraging .Net on Azure, with a strong focus on AI-driven solutions for document management, data extraction, tax research, and knowledge management.

Collaborating with Principal Product Owners, Principal Engineers, and cross-functional agile scrum teams, you will accelerate the delivery of AI-enabled cloud-first tools for the Tax & Legal business at KPMG.

In this role you will …
Drive AI Adoption:
Create AI-driven tools to processing and extract data from client documentation.
Automate workflows using AI agents.
Classify and process data with AI-assisted transformation.
Utilise AI for data preparation in data engineering.
Implement deep research toolsets for tax knowledge and advisory services.
Deliver Cloud Solutions:
Leverage Azure AI tools.
Build container or function-based applications.
Develop secure microservice-based architectures integrate via messaging frameworks like Service Bus.
Use Entity Framework with Azure SQL or NoSQL databases (Cosmos DB).
Embed Excellence:
Integrate delivery, security, and automated testing within DevOps processes.
Continuously enhance technical knowledge and share insights.
Leadership and Communication:
Oversee solution designs through information security, architecture, and data privacy reviews.
Promote continuous improvement in Lean Agile and Scaled SCRUM methodologies.
Foster a team-driven quality mindset.
Strategic Influence:
Provide insightful feedback to peers and junior team members.
Influence strategic technical and non-technical decisions.
Collaborate with directors, partners, and engagement teams to advance strategic opportunities.
You will have …
Deep Technical Expertise: Extensive experience in architecting, designing, specifying, and developing software.
Proven Track Record: Personally built POCs, mentored software engineers, and successfully delivered complex software projects.
Cloud Experience: Hands-on experience in building cloud-first solutions.
AI Knowledge: Ability to articulate clearly how generative AI can solve document management, workflow automation, and knowledge management challenges.
Collaborative Approach: Worked closely with enterprise architecture, information assurance, information security, and data privacy teams.
Programming Skills: Proficiency with modern object-oriented languages such as C# or Java.
Enterprise Expertise: Strong understanding of web services, enterprise messaging, and orchestration.
Data Modelling: Designed complex data models.
Continuous Delivery: Promoted and utilized continuous delivery tooling.
Security Practices: Understanding of secure coding and infrastructure best practices.
Communication: Outstanding skills, effectively collaborating with technical and non-technical stakeholders.
Quality Focus: Enthusiasm for delivering high-quality products and excellent user experiences.

You may have …
AI Systems: Built systems leveraging generative AI and machine learning.
Document Systems: Designed document management and workflow systems.
Process Automation: Deep understanding of process automation.
Cloud Applications: Experience with cloud platforms such as Azure, AWS, or GCP.
Containers & Serverless: Worked with Docker, Kubernetes, Function apps, or other serverless platforms.
CI/CD Tools: Experience with Git, Jenkins, GitHub, or Azure DevOps.
Front-End Frameworks: Developed with React, Angular, Blazor, or ASP.NET MVC.
ORM Tools: Used Entity Framework, Hibernate, or similar ORM tools.
NoSQL Databases: Experience with Cosmos DB, MongoDB, MarkLogic, or Cassandra.
Messaging Systems: Familiarity with messaging platforms like Service Bus, MQ, or Kafka.
Data Analytics: Experience in data analytics and business intelligence.
User Experience: Delivered accessible, user-friendly experiences.
Infrastructure as Code: Used infrastructure-as-code tools such as ARM, Bicep, or Terraform