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Full timeTechnology

AI Engineer - Data Science

AuwNew York🇺🇸United StatesPosted Oct 23, 2026

Why this role stands out

Join a high-impact AI team at United Risk where you will build transformative underwriting tools while sharpening your skills through direct mentorship from senior engineers. You will thrive in this collaborative, autonomous environment if you are a data-driven problem solver eager to convert complex datasets into actionable industry insights. With a highly competitive salary of up to $120,000, this is an exceptional opportunity to accelerate your career—apply today to shape the future of insurance technology.

Quick overview

Salary$100k - $120k/yr
SeniorityMid Senior
Employment typeFull Time
Work modeOn Site
LocationNew York, United States
PostedYesterday
ComplianceUnderwriting

Job description

United Risk is a global property and casualty insurance underwriting and distribution platform. It is independently owned and operated by its practice partners and affiliated with Applied Underwriters. Our practices cover specialty casualty and property, surety, financial lines, aviation, crisis and political risk, marine, fine art and more. Each one is led by underwriters who run their specialty with real autonomy.

Our AI team builds the tools that make those underwriters quicker and smarter. That includes submission ingestion, underwriting workbenches, risk analysis, and automation across the back and middle office. Our focus is to deliver tailored solutions to improve efficiency, while also maintaining our standards to security and compliance.

The Role:

You'll be one of a small group of AI Engineers. You'll work directly with underwriters and operations staff. You'll adapt the products we already run to their needs, and build new ones where nothing fits.

This role leans toward data science: turning our submission, policy and loss data into insight underwriters can act on. Everyone on the team also builds applications and works on infrastructure. Three senior AI engineers review your work and teach you along the way.