Senior Manager - Principal AI Engineer

Role Type: Hybrid working

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 allow audit workflows to become more efficient, enhance audit quality, and generate actionable insights for auditors and clients. Through cutting‑edge tools, we aim to transform traditional audit practices into dynamic, forward‑thinking processes designed for today’s complex business environment.

Supported by KPMG’s global network, our team drives this transformative journey. Focused on innovation, we engineer solutions that anticipate tomorrow’s challenges and opportunities, ensuring audit services stay at the forefront of technology.

As a Principal AI Engineer, you will transform advanced AI concepts into production‑ready solutions within the Audit Technology team. You will lead a dedicated AI engineering squad, collaborate with data scientists, data engineers, software developers, cloud architects, and audit professionals to build and scale AI‑driven systems that improve audit quality, efficiency, and insight generation.

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

Beyond technical leadership, you will shape team growth—mentoring engineers, championing best practices, and fostering a culture of collaboration, innovation, and continuous improvement. You will stay ahead of AI engineering trends, advocate modern development methodologies, and drive knowledge sharing across technology and audit domains.

• Leadership & Mentorship:
  Lead a high‑performing AI engineering team composed of 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, Lang Chain, and Lang Graph. 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 integrated 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 ope rationalising AI governance frameworks to ensure regulatory and ethical compliance.
• Capability Building & Knowledge Sharing:
  Drive initiatives that enhance internal capabilities, empowering team members and the broader Audit Technology function with the skills and knowledge required to adopt and adapt AI innovations effectively.

• Bachelor (preferably master or PhD) in Computer Science, Artificial Intelligence, Data Science, Statistics, Engineering, or a related technical field—or equivalent professional experience.
• Strong…