Overview

The Audit Technology team at KPMG blends audit expertise with cutting-edge technology to design robust, intelligent, and scalable solutions that improve audit quality and deliver actionable insights. We collaborate with Cloud & DevOps Engineers, Product Owners/Managers, Solution Architects, Data Engineers, Business Analysts, and Testing Specialists to build, deliver, and manage a portfolio of products. The team is expanding rapidly, with ambitious growth plans and a focus on staying current with the tech field and trends in audit delivery.

Base Location: London plus a network of 20 offices nationally. Core tech hubs for this role include Glasgow, Leeds, London Canary Wharf, and Manchester. Flexible working options may be available across the UK network.

What you will be doing

• Lead the technical delivery of AI projects within your squad, collaborating with data scientists, engineers, cloud architects, and audit professionals to create scalable AI systems that improve audit quality, efficiency, and insights.
• Develop robust proof-of-concepts and deploy enterprise-grade AI solutions, applying expertise in AI engineering, cloud platforms, and technologies such as Generative AI, Azure, and Databricks to embed intelligence into audit workflows and products.
• Mentor junior engineers, promote best practices, and foster a culture of collaboration, innovation, and continuous improvement. Stay at the forefront of AI engineering trends and drive knowledge-sharing across technology and audit domains.
• Collaborate with stakeholders to ensure AI capabilities are embedded within core audit platforms and services, including defining reusable development patterns, coding standards, and MLOps practices.
• Work significant time at client sites or KPMG offices as required by the role.

Responsibilities

• Lead by example: contribute to codebases and technical decisions while mentoring junior engineers.
• Scalable AI Engineering: develop and deploy production-grade AI systems for audit applications; contribute to architecture decisions and solution governance; write clean, scalable code aligned with software engineering principles, MLOps, and cloud-native development.
• AI Solution Delivery: own ML pipelines, APIs, and data integration workflows.
• Operational Excellence: define reusable development patterns, enforce coding standards, and implement MLOps best practices for version control, performance, and maintainability.
• Cross-Disciplinary Collaboration: work with data scientists, product managers, platform engineers, and QA to align requirements, delivery timelines, and integration plans; ensure AI capabilities are embedded in core audit platforms and services.
• Capability Building & Knowledge Sharing: contribute to internal capability-building and share practical AI skills and techniques across the team.

What you will need to do it

• Experience: Significant professional experience in backend development at a senior level.
• Languages/Frameworks: Strong Python proficiency with asynchronous programming, concurrency, and multithreading.
• API Expertise: Proven experience building and integrating APIs, with OpenAPI/Swagger for documentation; strong RESTful design and authentication/authorization knowledge; familiarity with Microsoft Graph API is a plus.

Experience & Knowledge

• Good knowledge of generative AI, machine learning, deep learning, NLP or related AI fields.
• Proven track record designing, developing, and deploying AI systems in production.
• Proficient in Python and ML libraries (e.g., PyTorch, PySpark, scikit-learn, Hugging Face Transformers).
• Hands-on experience with Azure ML, Databricks, MLflow, LangChain, LangGraph.
• Experience with modern engineering practices, Git, version control, unit testing, and containerisation.
• Familiarity with agile methodologies and tools like Jira and Confluence.

Behavioural Attributes and Skills

• Strong communication skills with the ability to explain technical concepts to varied audiences clearly.

Qualifications

• Bachelor, preferably Master or PhD, in Computer Science, AI, Data Science, Statistics, Engineering, or related field.
• Advanced certifications in AI, ML, cloud computing or data engineering are advantageous.
• Professional accounting qualification is desirable but not required.

Locations

We are open to talk to talent nationwide; core hubs for this role are Glasgow, Leeds, London Canary Wharf, and Manchester.

Additional info & applying

To discuss this or wider technology roles, apply through the standard KPMG recruitment process: create a profile, upload your CV, and begin your application. We provide flexible working options across the UK network and can discuss office work, working from home, flexible hours, and part-time arrangements during the process.