Lead Software Engineer, AI Platform

Root Insurance

66d•$164,200 - $240,000•Remote

About The Position

The AI Platform team builds the infrastructure, tooling, and operating patterns that make AI capabilities reliable, secure, and usable across Root’s products and operations. The Lead Software Engineer will guide the team building this foundation, set quarterly technical direction, coordinate dependencies, and coach engineers while remaining engaged in technical work. The role leads delivery of shared services, tools, deployment patterns, and operational practices; establishes technical priorities; and drives decisions about reliability, security, observability, cost, and developer experience. It also brings together product engineering, data, security, and platform partners, creates reusable team practices, supports engineers through complex work, and keeps stakeholders informed about progress, risks, and decisions. The role is open to candidates working from any location across the United States under Root’s “work where it works best” approach. Salary range: $164,200–$240,000, with eligibility for a competitive bonus and equity offering.

Requirements

At least 5 years of experience as a software engineer.
At least 1 year leading software teams or major technical initiatives.
Demonstrated ability to lead team-level technical delivery and make sound decisions in partially defined problem spaces.
Deep experience with cloud infrastructure, preferably AWS, Terraform, and modern DevOps practices.
Experience designing secure, observable, reliable systems and incorporating technical investments into team roadmaps.
Strong understanding of AI/LLM application and platform patterns, including operational and security implications.
Ability to identify cross-team dependencies, align stakeholders, and improve delivery outcomes.
A coaching mindset and a track record of helping teammates grow through complex technical work.
Clear written and verbal communication skills that drive team alignment and action.

Responsibilities

Lead delivery of shared AI services, tools, deployment patterns, and operational practices.
Set quarterly technical priorities that balance current user needs with foundational investments.
Drive decisions concerning reliability, security, observability, cost, and developer experience.
Coordinate with product engineering, data, security, and platform teams to resolve dependencies.
Establish reusable patterns for architecture, testing, documentation, and production operations.
Coach engineers through complex designs, delivery challenges, and technical tradeoffs.
Keep stakeholders informed about progress, risks, and decisions.