Senior AI Engineering Lead – Production-Scale ML & LLM Systems

MMC; New York (NY); Hybrid; USD 195,000 - 250,000; Full time

Benefits offered by this job

Hybrid work

Performance-based incentives

Job summary

Oliver Wyman Quotient is seeking a Senior Lead AI Engineer to lead and deliver AI/ML solutions for diverse client projects. You will design, build, and productionize AI systems, collaborate with partners and clients, and guide teams in scalable, auditable ML pipelines.

You will work across OW Quotient to explore data, select modeling approaches, and implement robust agent-based architectures while aligning with governance and risk considerations in financial services and other industries.

Qualifications

• Technical background in computer science, data science, ML, AI, statistics or other quantitative fields.
• Track record deploying large-scale AI systems delivering tangible value.
• Comfort with time-boxed projects and rapid design decisions.
• Fluency in modern AI programming languages and end-to-end AI lifecycle.
• Knowledge of agentic platforms (Azure Foundry, AWS Bedrock, Gemini).
• Familiarity with RAG, tool use, memory, and multi-agent orchestration.

Responsibilities

• Exploring data and crafting AI solutions to business problems.
• Shaping proposals with Partners to leverage AI capabilities.
• Building and deploying LLM-based agent systems in production.
• Staying current with domain advances and data engineering methodologies.
• Advocating best practices in modelling, code hygiene, and data engineering.
• Leading development of proprietary AI/ML solutions on projects.

Skills

AI/ML systems

Production deployment

LLM design

Prompt engineering

Agent platforms

Observability tooling

Programming (Python)

Data science fundamentals

Math foundations

Tools

Azure Foundry

AWS Bedrock

Gemini Enterprise

Job description

Oliver Wyman Quotient is seeking a Senior Lead AI Engineer to lead and deliver AI/ML solutions for diverse client projects. You will design, build, and productionize AI systems, collaborate with partners and clients, and guide teams in scalable, auditable ML pipelines.

You will work across OW Quotient to explore data, select modeling approaches, and implement robust agent-based architectures while aligning with governance and risk considerations in financial services and other industries.