Director, AI Engineering

What you will do

Lead end-to-end AI solution development or transformation programs using cloud AI services, enhancing customer experience, operational efficiency, and decision-making across various industries
Act as a trusted advisor to senior and C-level client stakeholders, shaping AI strategies and roadmaps while positioning KPMG’s AI solutions as strategic enablers of business objectives
Oversee the design, architecture, and delivery of multi-agent GenAI systems, advanced Retrieval-Augmented Generation (RAG) architectures, and multimodal solutions, ensuring seamless integration, quality, scalability, and security within enterprise workflows
Advise clients on AI Risk Management, Governance, and Security, ensuring GenAI deployments comply with emerging regulatory frameworks and enterprise security standards (e.g., implementing guardrails and defending against LLM vulnerabilities)
Drive business development to expand KPMG’s AI portfolio by identifying market opportunities, developing proposals, and securing new client engagements, while fostering strategic alliances
Manage and mentor cross-functional teams, promoting a high-performance culture, technical excellence, and career development, ensuring the team stays at the forefront of AI and cloud engineering technology advancements
Work closely with our Microsoft, Google, Salesforce, and other related platform teams to develop our AI capabilities and offerings within the relevant ecosystems
Set a clear strategic vision for AI strategy and engineering offerings, staying updated on the latest AI advancements (including frontier vs. open-weight models) and innovations, fostering a culture of innovation, and ensuring alignment with KPMG’s digital strategy
Act with integrity, professionalism, and personal responsibility to uphold KPMG’s respectful and courteous work environment

What you bring to the role

Minimum eight years of recent experience in AI/ML, data analytics, and cloud technology, including leadership roles in consulting or technology organizations; AI certifications (for example: Professional AI Architect, Machine Learning Engineer) or equivalent are a plus
Advanced degree from an accredited college or university in computer science, data science, engineering, or related field preferred; minimum of a Bachelor’s degree from an accredited college or university is required
Deep knowledge and hands-on experience with Microsoft, AWS, and/or Google Cloud’s AI ecosystem (including agent build functionality) to design and orchestrate intelligent multi-agent systems, integrating complex RAG pipelines, and connecting GenAI to proprietary enterprise data (Knowledge Graphs, Vector Databases) that handle complex, dynamic tasks and conversations
Proficient in architecting and implementing AI-powered workflow solutions using Microsoft, AWS, or Google Cloud services (For example: Foundry, Bedrock, Vertex AI), and demonstrating a strong grasp of model-agnostic architectures leveraging both proprietary and open-weight foundational models for scalable, automated systems with expertise in agentic AI and automation
Skilled in designing multi-agent conversational and autonomous AI systems integrated with enterprise applications (CRM, ERP), enhancing customer engagement through smart chatbots and virtual agents to improve user experience and operational efficiency; experienced in conversational AI integration
Deep understanding of scaling AI-driven solutions, GenAIOps/LLMOps (including LLM evaluation frameworks, prompt versioning, routing, and cost optimization), AI governance, and MLOps practices for maintaining models; ability to bring industry consulting insights with a balance of technical and business acumen to deliver strategic, value-driven AI solutions; In-depth knowledge of AI orchestration and best practices