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- Tasks: Lead a team to develop innovative AI solutions that transform auditing processes.
- Company: Join KPMG's Audit Technology team, driving innovation in audit delivery.
- Benefits: Hybrid working, competitive salary, and opportunities for professional growth.
- Other info: Collaborative environment focused on continuous improvement and innovation.
- Why this job: Make a real impact by shaping the future of audit with cutting-edge AI technology.
- Qualifications: Strong background in AI, software engineering, and leadership skills required.
The predicted salary is between 80000 - 100000 ÂŁ per year.
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.
As a Principal AI Engineer, you will play a pivotal role in transforming advanced AI concepts into impactful, production‑ready solutions within the Audit Technology team. You will lead a dedicated AI engineering squad, working closely with data scientists, data engineers, software developers, cloud architects, and audit professionals to build and scale AI‑driven systems that enhance audit quality, efficiency, and insight generation.
Responsibilities
- Leadership & Mentorship: Lead a high‑performing AI engineering team comprising software engineers and AI practitioners. Provide hands‑on technical direction, foster career growth, and cultivate a collaborative culture that emphasizes engineering excellence, innovation, and continuous improvement.
- Scalable AI Engineering: Drive the design, development and deployment of production‑grade AI systems tailored to audit applications. Ensure solutions are scalable, reliable, and maintainable by applying strong software engineering principles, MLOps practices, and cloud‑native development.
- End‑to‑End AI Solution Delivery: Oversee the full lifecycle of AI product engineering—from architectural design and prototyping to CI/CD‑enabled deployment—using modern platforms and tools such as Azure ML, Databricks, MLflow, LangChain and LangGraph.
- Operational Excellence: Define reusable development patterns, enforce coding standards, and promote MLOps best practices that support version control, performance optimisation and maintainability.
- Cross‑Disciplinary Collaboration: Partner closely with data scientists, product managers, platform engineers, and QA teams to align on technical requirements, delivery timelines, and integration plans.
- AI Governance & Risk Management: Implement engineering controls to support responsible AI use, including model monitoring, explainability, security and auditability.
- Capability Building & Knowledge Sharing: Drive initiatives to enhance internal capabilities, empowering team members and the broader Audit Technology function with the skills and knowledge to adopt and adapt AI innovations effectively.
Requirements
- Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field — or equivalent professional experience.
- Strong knowledge of generative AI, machine learning, deep learning, natural language processing and other relevant AI fields.
- Proven track record of designing, developing and deploying AI systems in production environments.
- Proficient in Python and key ML libraries (PyTorch, PySpark, scikit‑learn, Hugging Face Transformers).
- Hands‑on experience with modern data platforms and AI tooling such as Azure ML, Databricks, MLflow, LangChain and 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.
- Exceptional leadership and communication skills, with the ability to convey complex technical concepts to diverse audiences.
- Advanced certifications in AI, machine learning, cloud computing or data engineering are highly advantageous.
- Professional accounting qualification preferred, however not a requirement.
Senior Manager - Principal AI Engineer in London employer: hackajob
Contact Detail:
hackajob Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Manager - Principal AI Engineer in London
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with KPMG employees on LinkedIn. A personal touch can make all the difference when it comes to landing that interview.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects or contributions to open-source initiatives. This gives potential employers a taste of what you can bring to the table.
✨Tip Number 3
Prepare for those interviews! Research common questions for AI engineering roles and practice your responses. Don’t forget to have a few questions ready for them too—show you’re genuinely interested in their work!
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, you’ll be one step closer to joining a team that’s at the forefront of AI innovation.
We think you need these skills to ace Senior Manager - Principal AI Engineer in London
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with AI engineering and leadership. We want to see how your skills align with the role, so don’t hold back on showcasing your relevant projects!
Showcase Your Technical Skills: When detailing your experience, focus on the technologies mentioned in the job description, like Azure ML and Databricks. We love seeing specific examples of how you've used these tools to deliver impactful solutions.
Highlight Collaboration Experience: Since this role involves working closely with various teams, share examples of successful collaborations. We’re keen to know how you’ve partnered with data scientists or product managers to achieve common goals.
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. We can’t wait to see what you bring to the table!
How to prepare for a job interview at hackajob
✨Know Your AI Stuff
Make sure you brush up on your knowledge of generative AI, machine learning, and the specific tools mentioned in the job description like Azure ML and Databricks. Be ready to discuss your past projects and how you've applied these technologies in real-world scenarios.
✨Showcase Leadership Skills
As a Principal AI Engineer, you'll be leading a team. Prepare examples of how you've successfully led teams in the past, mentored others, and fostered a collaborative culture. Highlight your ability to communicate complex ideas clearly to different audiences.
✨Understand the Audit Landscape
Familiarise yourself with the auditing process and how AI can enhance it. Think about how your technical skills can solve specific challenges in audit technology. This will show that you understand the role's impact on the business.
✨Prepare for Technical Questions
Expect to dive deep into technical discussions during the interview. Brush up on coding standards, MLOps practices, and software engineering principles. You might even face some live coding or problem-solving scenarios, so practice those skills beforehand!