Director, AI Engineering

Role overview

What you will do

• Lead end-to-end AI solution development and transformation programs using cloud AI services to improve customer experience, operational efficiency, and decision-making.
• Advise senior and C-level client stakeholders on AI strategy and roadmaps, positioning AI solutions to support business objectives.
• Oversee architecture and delivery of multi-agent generative AI systems, RAG architectures, and multimodal solutions within enterprise workflows.
• Advise clients on AI risk, governance, and security, including regulatory compliance, guardrails, and defense against LLM vulnerabilities.
• Drive business development by identifying opportunities, developing proposals, securing client engagements, and fostering strategic alliances.
• Manage and mentor cross-functional teams, supporting performance, technical excellence, and career development.
• Work with Microsoft, Google, Salesforce, and other platform teams to develop AI capabilities and offerings.
• Set the strategic vision for AI engineering offerings, track AI advancements, and align with KPMG’s digital strategy.
• Act with integrity and professionalism and uphold a respectful work environment.

What you bring

• At least eight years of recent experience in AI/ML, data analytics, and cloud technology, including leadership roles in Banking and Capital Markets consulting.
• Bachelor’s degree from an accredited institution in computer science, data science, engineering, or a related field; an advanced degree is preferred.
• Deep hands-on knowledge of Microsoft, AWS, and/or Google Cloud AI ecosystems, including agent-building functionality.
• Experience designing multi-agent systems, complex RAG pipelines, and connections to enterprise data such as knowledge graphs and vector databases.
• Experience architecting AI-powered workflows with cloud services and model-agnostic systems using proprietary and open-weight models.
• Experience with agentic AI, automation, conversational AI, and integrations with CRM and ERP systems.
• Knowledge of GenAIOps/LLMOps, LLM evaluation, prompt versioning, routing, cost optimization, AI governance, and MLOps.
• AI certifications such as Professional AI Architect or Machine Learning Engineer, or equivalent, are a plus.

Technical scope

• The work includes cloud AI services, multi-agent systems, RAG, multimodal solutions, enterprise data integration, and conversational AI.
• The role covers AI governance and security, GenAIOps/LLMOps, MLOps, model evaluation, prompt versioning, routing, and cost optimization.

KPMG values