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- Tasks: Lead a team to create impactful AI solutions for audit technology.
- Company: Join a forward-thinking company at the forefront of AI innovation.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic role with a focus on collaboration and continuous improvement.
- Why this job: Shape the future of AI in auditing and mentor the next generation of engineers.
- Qualifications: Expertise in AI, cloud platforms, and strong leadership skills required.
The predicted salary is between 80000 - 100000 £ per year.
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. 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. In addition to technical leadership, you will shape the growth of the team – mentoring engineers, promoting best practices, and fostering 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.
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. Champion automation, testing, and observability across pipelines.
- 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. Ensure AI capabilities are well embedded within core audit platforms and services.
- AI Governance & Risk Management: Implement engineering controls to support responsible AI use, including model monitoring, explainability, security and auditability. Contribute to the operationalisation of AI governance frameworks to ensure regulatory and ethical compliance.
- 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.
Qualifications
- 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 (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.
- 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 Birmingham employer: KPMG International Cooperative
Contact Detail:
KPMG International Cooperative Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Manager - Principal AI Engineer in Birmingham
✨Tip Number 1
Network like a pro! Get out there and connect with folks in the AI and audit space. Attend meetups, webinars, or even just grab a coffee with someone in the industry. You never know who might have the inside scoop on job openings or can put in a good word for you.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that highlight your experience with tools like Azure ML and Databricks. This will give potential employers a taste of what you can bring to the table and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and soft skills. Be ready to discuss your past experiences leading teams and delivering AI solutions. Practice common interview questions and think about how you can demonstrate your leadership and mentorship abilities.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Make sure your application reflects your passion for AI and your ability to drive innovation in audit technology. Let’s get you on board!
We think you need these skills to ace Senior Manager - Principal AI Engineer in Birmingham
Some tips for your application 🫡
Tailor Your CV: Make sure your CV reflects the skills and experiences that align with the Principal AI Engineer role. Highlight your expertise in AI engineering, cloud platforms, and any relevant projects you've led or contributed to.
Craft a Compelling Cover Letter: Use your cover letter to tell us why you're passionate about AI and how you can contribute to our Audit Technology team. Share specific examples of your leadership and mentorship experiences to show us what you bring to the table.
Showcase Your Technical Skills: Don’t shy away from listing your technical proficiencies! Mention your experience with tools like Azure ML, Databricks, and any programming languages you excel in, especially Python. We want to see your hands-on experience!
Apply Through Our Website: We encourage you to apply directly through our website for a smoother application process. It’s the best way for us to receive your application and get you into our system quickly!
How to prepare for a job interview at KPMG International Cooperative
✨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 Senior Manager, you'll need to demonstrate your leadership abilities. Prepare examples of how you've mentored teams, fostered collaboration, and driven innovation in previous roles. Highlight any initiatives you've led that improved team performance or project outcomes.
✨Understand the Audit Landscape
Familiarise yourself with the audit technology space and how AI can enhance audit quality and efficiency. Be prepared to discuss how your technical expertise can translate into impactful solutions for audit professionals and the broader organisation.
✨Prepare for Technical Questions
Expect in-depth technical questions related to AI engineering and software development practices. Brush up on MLOps, CI/CD processes, and coding standards. Practising coding challenges or system design questions can also help you feel more confident during the interview.