At a Glance
- Tasks: Lead AI projects, develop scalable systems, and mentor junior engineers in a collaborative environment.
- Company: Join KPMG's innovative Audit Technology team reshaping the future of auditing.
- Benefits: Flexible working options, competitive salary, and opportunities for professional growth.
- Other info: Dynamic work culture with excellent career advancement opportunities across multiple UK locations.
- Why this job: Be at the forefront of AI engineering and make a real impact on audit quality.
- Qualifications: Strong Python skills, experience in AI systems, and a background in computer science or related fields.
The predicted salary is between 63000 - 77000 £ per year.
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 growth has 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.
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.
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 in a hands-on capacity, actively contributing to codebases and technical decisions while mentoring junior engineers.
- 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.
- Own the implementation of ML pipelines, APIs, and data integration workflows.
- Contribute to defining reusable development patterns, enforcing coding standards, and implementing MLOps best practices that support version control, performance optimisation, and maintainability.
- 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.
- 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?
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.
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.
Manager - Lead AI Engineer employer: KPMG LLP
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StudySmarter Expert Advice🤫
We think this is how you could land Manager - Lead AI Engineer
✨Join Local Tech Meetups
Get out there and mingle with fellow developers by joining local tech meetups. It’s a fantastic way to meet people who might be working at KPMG LLP or know someone who does. Plus, you can pick up some trendy tech skills and trends while you're at it!
✨Contribute to Open Source Projects
Show off your coding chops by jumping into open-source projects. Not only does this give you practical experience, but it also gets you noticed in the dev community. You'll create a killer portfolio that speaks volumes about your skills to KPMG LLP.
✨Tap into Online Developer Communities
Don’t underestimate the power of online developer communities like GitHub, Stack Overflow, and even Reddit. Participate in discussions, share your projects, and build your visibility. We can often find opportunities through these channels that can lead to a full-time gig at companies like KPMG LLP.
✨Explore Job Boards Specifically for Tech Roles
Keep your eyes peeled on job boards that focus on tech roles. Sites like TechCareers or Stack Overflow Jobs can often have listings for companies like KPMG LLP that might not show up on broader job sites. Make it a habit to check these regularly, and don’t hesitate to apply directly through our website!
We think you need these skills to ace Manager - Lead AI Engineer
Some tips for your application 🫡
Show off your coding skills:When applying for a software engineering role, it's super important to showcase your coding skills. Make sure your CV includes your tech stack, any relevant programming languages you’re comfortable with, and examples of projects you've worked on. If you have a GitHub profile, link it up! We love to see code in action.
Tailor your portfolio:For a full-time role, we’d expect to see some solid examples of your work in your portfolio. Make sure to include at least two or three projects that highlight your problem-solving skills and your ability to work with different technologies. Focus on the projects that are most relevant to the position at KPMG LLP.
Craft a killer cover letter:Your cover letter is your chance to stand out—make it personal! Explain why you want to work at KPMG LLP and how your skills align with the role. Show us your passion for software development. We dig enthusiastic candidates who understand the value of collaboration and continuous learning!
Be clear and concise:When it comes to writing your CV and cover letter, clarity is key. Avoid jargon that could confuse us and stick to simple, direct language. Highlight your achievements with quantifiable results where possible, and keep everything easy to read. A well-organised application goes a long way!
How to prepare for a job interview at KPMG LLP
✨Brush Up on Your Coding Skills
For a full-time software engineering role, it's crucial that we stay sharp with our coding abilities. Expect technical questions that might involve solving problems on the spot or discussing algorithms. Practise on platforms like LeetCode or HackerRank to get comfortable with the types of questions that often come up.
✨Know Your Tools and Frameworks
Make sure we’re well-acquainted with the tools and technologies listed in the job description. Familiarise ourselves with any specific frameworks or programming languages mentioned. If KPMG LLP uses React or Node.js, for instance, be ready to discuss how we’ve used them in previous projects or coursework.
✨Showcase Your Projects
Bring along a portfolio that highlights our best work. This could be code samples, GitHub repositories, or any side projects we’ve built. Make sure we can talk through our thought process for each project, especially the challenges we faced and how we solved them—this shows our problem-solving skills in action.
✨Prepare for Behavioural Questions
While technical skills are key, full-time positions also require cultural fit. Be ready to discuss our previous experiences and how we handle teamwork, conflict, and deadlines. Brush up on the STAR method—Situation, Task, Action, Result—to clearly articulate our past experiences when discussing how we've contributed to a team.
