Senior Lead AI Engineer — Build Production-Ready AI Systems

Marsh McLennan; Washington; Hybrid; USD 195,000 - 250,000; Full time

Benefits offered by this job

Health and welfare benefits

Tuition assistance

401K and retirement programs

Job summary

Oliver Wyman Quotient is hiring a Senior Lead AI Engineer in a hybrid setting across OW offices in the US. You will manage technical AI projects and guide teams to design and deploy AI/ML systems that are scalable and production-ready, working directly with clients and partners.

You should have a strong technical background in AI/ML, experience deploying large-scale solutions, and fluency with modern AI development lifecycles including prompt engineering and evaluation frameworks.

Qualifications

• Technical background in computer science, data science, machine learning, artificial intelligence, statistics or related fields.
• Experience designing and deploying large-scale technical AI solutions that are production-ready.
• Fluency in modern programming languages for AI/agents and familiarity with agentic platforms.

Responsibilities

• Explore data and craft AI solutions to address core business problems.
• Collaborate with Partners to shape proposals leveraging AI and engineering capabilities.
• Build and deploy LLM-based agent systems in production.
• Maintain awareness of advances in modeling and data engineering methodologies.
• Lead development of proprietary AI/ML solutions and tools on projects.

Skills

AI/ML systems

Production-grade AI

Data science & statistics

System architecture

Programming for AI agents

Education

Computer Science or related field

Tools

Azure Foundry

AWS Bedrock

Gemini Enterprise Agent Platform

Job description

Oliver Wyman Quotient is hiring a Senior Lead AI Engineer in a hybrid setting across OW offices in the US. You will manage technical AI projects and guide teams to design and deploy AI/ML systems that are scalable and production-ready, working directly with clients and partners.

You should have a strong technical background in AI/ML, experience deploying large-scale solutions, and fluency with modern AI development lifecycles including prompt engineering and evaluation frameworks.