Senior Manager, Principal AI Engineer

- 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.