Engineering Manager

The Engineering AI Team Lead owns the technical delivery of AI solutions, ensuring they are robust, scalable, and production-ready. This role blends leadership, hands‑on engineering, and architectural oversight. You will mentor engineers and data scientists, set technical standards, and ensure that product requirements are translated into reliable solutions. Beyond delivery, you will help scale AI adoption across the firm by building engineering patterns, reusable services, and blueprints to drive adoption and scale AI across the firm. Your contribution to KPMG Engineering Coordination & Development Coordinate and develop within a high-performing team of AI engineers and data scientists. Foster a culture of inclusion, continuous learning, and technical excellence. Technical Strategy & Execution Define the engineering approach and architecture for AI solutions and services. Evaluate and adopt the right tools and frameworks to meet product requirements. Ensure solutions are designed for scalability, security, and maintainability. Project Delivery Translate product requirements into technical deliverables. Manage planning, resourcing, and execution of engineering work on Azure. Oversee delivery quality, risk management, and timelines. Hands‑On Engineering Contribute to architecture and code reviews, and resolve complex technical challenges. Build and optimize ML pipelines, reusable services, deployment workflows, and MLOps/DevOps automation. Stay up to date with ML, GenAI, and infrastructure best practices. Governance & Best Practices Define coding standards, CI/CD pipelines, testing protocols, and documentation. Ensure compliance with privacy, security, and responsible AI guidelines. Promote operational reliability and maintainability. Enablement & Adoption Develop engineering services, patterns, and blueprints to drive adoption and scale AI across the firm. Share technical knowledge through documentation, training, and community‑building. Enable reusability and consistency of AI solutions across teams. This is what makes you successful Bachelor’s or Master’s in Computer Science, Machine Learning, or related field. 5+ years in AI/ML engineering, with 2+ years in a leadership role. Strong programming in Python and proficiency with ML frameworks (PyTorch, TensorFlow). Hands‑on expertise in Azure AI/ML services (Azure ML, Azure DevOps, AKS). Practical experience with GenAI/LLMs (prompt engineering, RAG basics). Proven delivery across the full AI lifecycle: experimentation → deployment → monitoring. Strong communication and leadership skills in cross‑functional environments. Discover KPMG – Become part of our teamThe AI CoE team is a cross‑functional group dedicated to driving innovation, best practices, and scalable adoption of artificial intelligence across the organization. This team brings together experts in product management, engineering, data science, and business strategy to define the vision and roadmap for AI‑powered solutions. The AI CoE ensures that AI initiatives deliver measurable business value, align with enterprise priorities, and adhere to responsible AI governance.With 300 different auditing and advisory service opportunities, our people can choose the career path that suits them best. Through our competencies in business transformation as well as ESG consulting, we support our clients in today's biggest challenges. We are a purpose‑led and values‑driven company where your insight can create opportunities for you and contribute to a better future. Do work that matters, supported by a community that values difference and cares about you. Gain learning that'll last you a lifetime and be recognized for the impact you make. Find opportunity everywhere with KPMG. #J-18808-Ljbffr