Assistant Manager - Senior AI Engineer

Location: 

London

Category:  Central Audit
Business Unit: 

 

Assistant Manager - Senior AI Engineer

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 Senior 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.

 

Summary of role purpose:

  • Contribute to the design, build, and deployment of scalable AI and Generative AI solutions within core audit platforms.
  • Support delivery of AI engineering initiatives, ensuring high-quality, maintainable, and production-ready solutions.
  • Work closely with cross-functional teams to integrate AI capabilities into products and services.
  • Support capability development within the team by sharing knowledge and contributing to best practices in AI engineering and AI-native development.

 

Description of the role:

  • Scalable AI Development: Design, develop, and deploy AI systems for audit use cases, producing clean, efficient, and scalable code aligned to software engineering principles, LLMOps practices, and cloud-native development.
  • AI-Powered Delivery: Support the implementation of AI pipelines, APIs, and data integration workflows, leveraging an AI-Native Engineering approach and tools such as Claude Code and GitHub Copilot.
  • Operational Excellence: Follow established development patterns and standards, contributing to LLMOps practices including version control, monitoring, evaluation, and performance optimisation of AI solutions.
  • Cross-Disciplinary Collaboration: Work closely with product managers, engineers, and QA teams to deliver integrated AI solutions aligned to requirements and timelines.
  • Knowledge Sharing: Contribute to team capability through knowledge sharing, supporting peers, and promoting the use of reusable components and best practices.

Due to the nature of the position, you may be working at/visiting a client site and/or other KPMG offices.

 

The person:

Experience and knowledge requirements:

•            Experience delivering AI/ML solutions, including experience deploying solutions in production environments, with a focus on quality and scalability (E)

•            Solid foundation in AI engineering, including AI/ML lifecycle concepts, generative AI applications, and system design (E)

•            Experience delivering rapid prototypes and proof-of-value solutions, translating ideas into working solutions under tight timelines (E)

•            Strong Python expertise with hands-on experience in modern AI/ML frameworks and libraries (e.g. LangChain, LangGraph, Microsoft Agent Framework, Pydantic, PyTorch, Spark) (E)

•            Familiarity with modern engineering practices, including Git and version control, with an understanding of branching strategies, code reviews, and collaborative development workflows. (E)

•            Exposure to LLMOps practices, including prompt and model versioning, evaluation frameworks, monitoring, and performance optimisation (E)

•            Experience with cloud and data platforms, such as Azure, Databricks, or similar (E)

•            Experience in regulated or enterprise environments (e.g. financial services, audit, public sector) (D)

•            Experience working with AI development tools (e.g. GitHub Copilot, Claude Code, or similar) (D)

D = Desirable   E = Essential

 

Behavioural Attributes and Skills:

•            Strong problem-solving skills with attention to detail

•            Collaborative and team-oriented mindset

•            Eager to learn and adapt in a fast-evolving AI landscape

•            Ability to communicate technical concepts clearly to a range of stakeholders

•            Delivery-focused with a pragmatic approach to engineering challenges

 

Qualifications:

•            Bachelor’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Statistics, or related field (E)

•            Master’s or PhD in a relevant discipline (D)

•            Advanced certifications in AI, Machine Learning, Cloud (e.g., Azure), or Data Engineering (D)

D = Desirable     E = Essential

 

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:

Within Tech and Engineering we have a range of divisions and specialisms.  Click the links to find out more below:

Technology and Engineering at KPMG: www.kpmgcareers.co.uk/experienced-professional/technology-engineering/

ITs Her Future Women in Tech programme: www.kpmgcareers.co.uk/people-culture/it-s-her-future/

KPMG Workability and Disability confidence: www.kpmgcareers.co.uk/experienced-professional/applying-to-kpmg/need-support-let-us-know/

For any additional support in applying, please click the links to find out more:

Applying to KPMG: www.kpmgcareers.co.uk/experienced-professional/applying-to-kpmg/

Tips for interview: www.kpmgcareers.co.uk/experienced-professional/applying-to-kpmg/application-advice/

KPMG values: www.kpmgcareers.co.uk/experienced-professional/applying-to-kpmg/our-values/

KPMG Competencies: www.kpmgcareers.co.uk/experienced-professional/applying-to-kpmg/kpmg-competencies/

KPMG Locations and FAQ: www.kpmgcareers.co.uk/faq/?category=Experienced+professionals