Associate Director - Engineering (Cloud & AI Solutions)

Associate Director _ UK Engineering

1. 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.

1. 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.

1. 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.

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1. 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

Experience Level

Mid Level