Manager - Lead AI Engineer

Job description

Base Location: London plus network of 20 offices nationally:

The KPMG Audit Technology team is dedicated to building cutting-edge solutions in close collaboration with the Audit function. We blend audit expertise with the latest technology, enabling us to understand the challenges our customers face daily and develop indispensable products that simplify their lives while promoting Audit Quality.

As a crucial member of the team, you will collaborate with a talented mix of Cloud & DevOps Engineers, Product Owners/Managers, Solution Architects, Data Engineers, Business Analysts, and Testing Specialists. Together, we build, deliver, and manage a portfolio of truly exciting products.

In recent years, our products' size and scale have rapidly expanded, leading to significant growth in our technology capability. There's never been a better time to join us.

With our ambitious growth plans, your future here is something to get excited about. As a valued team member, you'll be expected to stay current with the tech field and the latest trends in Audit delivery.

Why Join KPMG As a Lead AI Engineer?

The Audit Technology team at KPMG is driving innovation at the intersection of auditing and advanced technological solutions, reshaping the future of audit delivery. By combining expertise in Artificial Intelligence, Data Engineering, Data Analytics, and Software Development, the team is revolutionising the auditing process to deliver smarter, faster, and more reliable outcomes.

Our mission is to design and implement robust, intelligent, and scalable technologies that not only streamline workflows but also enhance audit quality and generate actionable insights for auditors and clients. Through harnessing the power of cutting-edge tools, we aim to transform traditional audit practices into dynamic, forward-thinking processes that are built for the complexities of the modern business environment.

Our team, supported by KPMG’s global network, serves as the driving force behind this transformative journey. Focused on innovation, this team is dedicated to engineering solutions today that anticipate the challenges and opportunities of tomorrow, ensuring that audit services remain at the forefront of technological progression.

What will you be doing?

As a Lead AI Engineer, you will report to AI Engineering Squad Lead and lead the technical delivery of AI projects within your squad, collaborating with data scientists, engineers, developers, cloud architects, and audit professionals to create scalable AI systems that improve audit quality, efficiency, and insights.

From developing robust proof-of-concepts to deploying enterprise-grade solutions, you will apply your expertise in AI engineering, cloud platforms, and technologies such as Generative AI, Azure, Databricks to embed intelligence into critical audit workflows and products.

You will mentor junior engineers, promote best practices, and foster a culture of collaboration, innovation, and continuous improvement. You will stay at the forefront of AI engineering trends, advocate for modern development methodologies, and drive knowledge-sharing across both the technology and audit domains.

Due to the nature of the role significant time may be spent at client sites/KPMG offices.

Responsibilities

Lead by Example: Lead by example in a hands-on capacity, actively contributing to codebases and technical decisions while mentoring junior engineers.

Scalable AI Engineering: Develop and deploy production-grade AI systems tailored to audit applications. Contribute to architectural decisions and solution governance. Write clean, efficient, and scalable code that adheres to software engineering principles, MLOps practices, and cloud-native development.

AI Solution Delivery: Own the implementation of ML pipelines, APIs, and data integration workflows.

Operational Excellence: Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability.

Cross-Disciplinary Collaboration: Work side-by-side with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans. Provide hands-on contributions to ensure AI capabilities are smoothly embedded within core audit platforms and services.

Capability Building & Knowledge Sharing: Contribute to internal capability-building initiatives and empower team members and the broader Audit Technology function by sharing practical skills and innovative techniques for adopting and adapting AI effectively.

What will you need to do it?

Minimum Requirements

• Experience: Significant professional experience in backend development as a Senior role.
• Languages/Frameworks: Strong proficiency in Python with hands-on experience in asynchronous programming, concurrency and multithreading.
• API Expertise: Proven experience in building and integrating APIs, with expertise in API documentation and schema definition using OpenAPI/Swagger. Strong understanding of RESTful API design, authentication/authorization standards, and API lifecycle best practices; familiarity with Microsoft Graph API is a plus.

Experience & Knowledge Requirements

• 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.
• Proficient in Python and key ML libraries (e.g. PyTorch, PySpark, scikit-learn, Hugging Face Transformers).
• Hands-on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain, LangGraph.
• Proven experience with modern engineering practices Git, version control, unit testing and containerisation.
• Familiarity with agile work methodologies and tools like Jira and Confluence.

Behavioural Attributes and Skills:

• Strong communication skills, with the ability to explain technical concepts to varied audiences in a clear and accessible manner.

Qualifications:

• Bachelor (preferably master 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 - desirable
• Professional accounting qualification preferred, however not a requirement - desirable

To discuss this or wider Technology roles with our recruitment team, all you need to do is apply, create a profile, upload your CV and begin to make your mark with KPMG.

Our Locations:

We are open to talk to talent across the country but our core Tech hubs for this role are:

• Glasgow
• Leeds
• London Canary Wharf
• Manchester

With 20 sites across the UK, we can potentially facilitate office work, working from home, flexible hours, and part-time options. If you have a need for flexibility, please register and discuss this with our team.

Find out more:

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