Senior Lead AI Engineer

About the role

Oliver Wyman Quotient partners with clients on their toughest AI challenges, blending AI technology with deep industry expertise. As a Senior Lead AI Engineer, you manage technical projects and help teams design and build AI/ML systems and pipelines that are extensible and production quality. You work alongside partners in Quotient and other practice groups, engage directly with clients and deliver solutions through collaboration with other specialists and consultants. The role is open to Oliver Wyman offices including New York, Boston, Chicago and DC.

Key responsibilities

• Explore data and craft AI solutions to answer core business problems
• Work with Partners and Principals to shape proposals that leverage AI and engineering capabilities
• Build and deploy LLM-based agent systems in production
• Keep up with the state of the art and emerging modelling and data engineering methodologies
• Advocate best practices in modelling, code hygiene and data engineering
• Lead the development of proprietary AI/ML solutions, algorithms, analytical tools and infrastructure

Required profile

• Technical background in computer science, data science, machine learning, AI, statistics or another quantitative field
• Track record of designing and deploying large-scale technical solutions, including complex production systems running modern AI at scale
• Comfort in time-boxed, high-consequence project environments
• Strong theoretical grounding in the mathematics of AI/ML (statistics, linear algebra, vector calculus)
• Experience presenting at high-impact AI/ML conferences and strong community connections are highly valued
• Interest in Financial Services, Healthcare, Consumer, Retail, Energy or Transportation is valued

Required skills

• Modern programming languages for AI and agents, end-to-end development lifecycle
• Agentic platforms such as Azure Foundry, AWS Bedrock and Gemini Enterprise Agent Platform
• Compound AI systems: RAG, tool use, agentic memory, multi-agent orchestration
• Evaluation frameworks and observability tooling for AI systems
• LLM system design: prompt engineering, context and token management, structured output, fine-tuning tradeoffs, cost and latency optimization
• Awareness of AI risk, bias and governance

What we offer

• Base salary range of $195K to $250K USD, depending on experience, skills, location, certifications and education
• Possible performance-based incentives
• Health and welfare benefits, tuition assistance, 401K and other retirement programs, and employee assistance programs
• Hybrid work, with at least three days per week in the office or onsite with clients