Senior Manager – Principal AI Engineer

Overview

In this role you shape and scale AI-powered audit technologies within KPMG’s Audit Technology team. You lead an AI engineering squad to deliver production-grade AI solutions that enhance audit quality and efficiency, collaborating with data scientists, engineers, cloud architects, and auditors. You’ll guide concept-to-production workflows, leveraging Azure and Databricks to embed intelligence into critical audit processes. Expect a culture of collaboration, continuous improvement, and responsible AI governance that supports measurable impact and regulatory compliance. This is a growth-driven, cross-disciplinary opportunity to influence how modern audits are delivered.

Responsibilities

• Lead a high-performing AI engineering team, providing technical direction and mentorship
• Design, develop, and deploy production-grade AI systems tailored to audit applications with a focus on scalability and reliability
• Oversee end-to-end AI product delivery from architecture and prototyping to CI/CD deployment using modern platforms (Azure ML, Databricks, MLflow, LangChain, LangGraph)
• Establish reusable development patterns, coding standards, and MLOps practices to ensure maintainability and performance
• Foster cross-disciplinary collaboration with data scientists, product managers, platform engineers, and QA to align requirements and integration plans
• Implement AI governance and risk management controls, including monitoring, explainability, and security
• Drive capability-building initiatives to upskill the Audit Technology function in AI innovations

Key requirements

• Bachelor in Computer Science (or related field); Master/PhD preferred
• Strong knowledge of generative AI, ML, DL, NLP
• Proven track record designing and deploying AI systems in production
• Proficiency in Python and ML libraries (PyTorch, PySpark, scikit-learn, Hugging Face Transformers)
• Hands-on experience with Azure ML, Databricks, MLflow, LangChain, LangGraph
• Experience with Git, unit testing, containerisation
• Familiarity with agile methodologies and tools (Jira, Confluence)
• Exceptional leadership and communication skills
• Advanced AI/cloud/data engineering certifications are advantageous
• Professional accounting qualification preferred but not required

• leadership
• communication
• collaboration
• Generative AI
• Machine Learning
• Deep Learning

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