Technical Program Lead, AI/ML

Marsh McLennan•New York, NY

2d•$139,500 - $278,900•Hybrid

About The Position

Marsh is seeking a highly experienced Technical Program Lead, AI/ML to provide principal-level technical leadership for digital experience and application development initiatives supporting its CFO organization. Based in Marsh’s US main office, this strongly hands-on role helps guide architecture, engineering standards, technical design, and delivery across AI, ML, data, and application engineering efforts. The role will help shape enterprise digital products in a high-performance, product-oriented environment. The position provides technical leadership for digital products, applications, and AI/ML-enabled platforms while remaining actively involved in architecture, design and code reviews, prototyping, troubleshooting, and complex engineering challenges. It guides engineering direction across a technology stack that includes Python, FastAPI, ReactJS, Kubernetes, Docker, MongoDB, PostgreSQL, GitHub, CI/CD, unified pipelines, and Databricks. The role partners with data and ML engineers on forecasting, predictive analytics, and finance-oriented data workflows, and mentors engineers while influencing technical direction across multiple workstreams. Marsh offers professional development opportunities, interesting work, supportive leaders, an inclusive culture, and career opportunities. The position is hybrid: colleagues are expected to work in their local office or onsite with clients at least three days per week, and office-based teams identify at least one weekly anchor day for in-person collaboration. The applicable base salary range is $139,500 to $278,900, with possible performance-based incentives. The total rewards package includes health and welfare benefits, tuition assistance, 401(k) savings and other retirement programs, and employee assistance programs.

Requirements

15+ years of software engineering experience.
A strong track record as a principal engineer, distinguished technical lead, or senior architect-level engineer.
Deep hands-on expertise in modern application, platform, and digital product engineering.
Strong experience with Python, FastAPI or equivalent backend frameworks, and ReactJS or similar frontend technologies.
Strong experience with Kubernetes, Docker, MongoDB, PostgreSQL, CI/CD, and Git-based workflows.
Experience with Databricks, ML-enabled products, forecasting or predictive use cases, and AI/agentic solutions such as LangChain and GPT-based applications.
Strong understanding of software architecture, observability, scalability, security, and production operations.
Demonstrated ability to mentor engineers and provide technical direction across multiple workstreams.

Nice To Haves

Experience at big-tech companies or similarly strong product engineering organizations.
Experience building enterprise digital products with a strong user experience and application engineering orientation.
Familiarity with finance, FP&A, controllership, or financial reporting-related systems.
Experience in modernization, refactoring, and technical uplift of engineering environments.
Familiarity with MLOps, AI observability, and model or application lifecycle tooling.
Strong stakeholder partnership skills across product, engineering, design, and business teams.
Experience influencing engineering culture, technical standards, and platform direction beyond one immediate team.

Responsibilities

Provide principal-level technical leadership for the design and delivery of digital products, applications, and AI/ML-enabled platforms.
Remain hands-on in architecture, design reviews, code reviews, prototyping, troubleshooting, and solving complex engineering challenges.
Guide engineering direction across solutions using Python, FastAPI, ReactJS, Kubernetes, Docker, MongoDB, PostgreSQL, GitHub, CI/CD, unified pipelines, and Databricks.
Partner with data and ML engineers to support forecasting, predictive analytics, and finance-oriented data workflows.
Mentor engineers, influence technical direction across multiple workstreams, and elevate engineering practices across the team.