Lead AI Engineer

Salary: £57,000 - 63,000 per year Requirements: • Significant professional experience in backend development at a senior level. • Strong proficiency in Python, including asynchronous programming, concurrency, and multithreading. • Proven experience building and integrating APIs, including API documentation and schema definition using OpenAPI/Swagger. • Strong understanding of RESTful API design, authentication/authorization standards, and API lifecycle best practices. • Good knowledge of generative AI, machine learning, deep learning, natural language processing, or other relevant AI fields. • Proven track record of designing, developing, and deploying AI systems in production environments. • Proficiency with key ML libraries such as PyTorch, PySpark, scikit-learn, and Hugging Face Transformers. • Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, and LangGraph. • Experience with modern engineering practices including Git, version control, unit testing, and containerisation. • Familiarity with agile methodologies and tools such as Jira and Confluence. • Strong communication skills with the ability to explain technical concepts clearly to varied audiences. • Bachelors degree, preferably a Masters or PhD, in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field. • Advanced certifications in AI, machine learning, cloud computing, or data engineering are highly advantageous. • Professional accounting qualification is preferred but not required. Responsibilities: • Lead the technical delivery of AI projects within our squad and collaborate with data scientists, engineers, developers, cloud architects, and audit professionals. • Develop and deploy production-grade AI systems tailored to audit applications. • Contribute to architectural decisions and solution governance. • Write clean, efficient, and scalable code following software engineering principles, MLOps practices, and cloud-native development. • Own the implementation of ML pipelines, APIs, and data integration workflows. • Contribute to defining reusable development patterns, coding standards, and MLOps best practices. • Support version control, performance optimisation, and maintainability. • Work closely with data scientists, product managers, platform engineers, and QA teams to align technical requirements, delivery timelines, and integration plans. • Provide hands-on contributions to ensure AI capabilities are embedded within core audit platforms and services. • Mentor junior engineers and contribute to internal capability-building initiatives. • Share practical skills and innovative techniques to help our wider Audit Technology function adopt and adapt AI effectively. • Stay at the forefront of AI engineering trends and advocate for modern development methodologies. Technologies: • AI • API • Azure • Backend • Cloud • Confluence • Databricks • Embedded • Git • Support • JIRA • Machine Learning • MLflow • MLOps • Network • OpenAPI • PyTorch • Python • PySpark • Swagger • DevOps More: We are KPMGs Audit Technology team, building cutting-edge solutions in close collaboration with our Audit function to improve audit quality and simplify day-to-day work. We combine audit expertise with the latest technology and are driving innovation at the intersection of auditing, AI, data engineering, analytics, and software development. This Lead AI Engineer role is based in London, with core tech hubs in Glasgow, Leeds, London Canary Wharf, and Manchester, and we support flexible working arrangements where possible. Our team works across a network of 20 UK offices and collaborates with a broad mix of technical and audit specialists, backed by KPMGs global network. This is an exciting time to join us as our products and technology capability continue to grow rapidly. last updated 33 week of 2026