The Opportunity

AI Platform is Root’s team for building the infrastructure, tooling, and operating patterns that make AI capabilities reliable, secure, and usable across Root’s products and operations. As a Lead Software Engineer on AI Platform, you will guide the team building this foundation, set quarterly technical direction, coordinate dependencies, and coach engineers while remaining close to the hard technical work.

Salary Range: $164,200 - $240,000 (Eligible for competitive bonus and equity offering)

Root is a "work where it works best" company. This means we will support you working in whatever location that works best for you across the US.

How You Will Make an Impact

• Turn a promising AI foundation into a capability Root teams can count on by leading delivery of shared services, tools, deployment patterns, and operational practices.
• Set quarterly technical priorities that balance today’s user needs with the foundational investments that unlock tomorrow’s products and workflows.
• Make AI easier to adopt and safer to operate by driving clear decisions on reliability, security, observability, cost, and developer experience.
• Bring the right partners together across product engineering, data, security, and platform teams to resolve dependencies before they slow delivery.
• Create reusable team patterns for architecture, testing, documentation, and production operations so good decisions scale beyond a single project.
• Grow the team’s technical capacity by coaching engineers through complex designs, delivery challenges, and the tradeoffs that matter.
• Build trust in the platform by keeping stakeholders clear on progress, risks, and the decisions that will improve outcomes.

What You Will Need to Succeed

• 5+ years as a software engineer
• 1+ years 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 their operational and security implications.
• Ability to identify cross-team dependencies, align familiar stakeholders, and improve delivery outcomes.
• A coaching mindset and track record of helping teammates grow through complex technical work.
• Clear written and verbal communication that drives alignment and action for a team.

As part of Root's interview process, we kindly ask that all candidates be on camera for virtual interviews. This helps us create a more personal and engaging experience for both you and our interviewers. Being on camera is a standard requirement for our process and part of how we assess fit and communication style, so we do require it to move forward with any applicant's candidacy. If you have any concerns, feel free to let us know once you are contacted. We’re happy to talk it through.

Please see our Privacy Notice available HERE for more information on how we process your personal data.

Consistent with the Americans with Disabilities Act (ADA) and the Civil Rights Act of 1964, it is the policy of Root to provide reasonable accommodation when requested by a qualified applicant or candidate with a disability, unless such accommodation would cause an undue hardship for Root. The policy regarding requests for reasonable accommodation applies to all aspects of the hiring process. If reasonable accommodation is needed, please contact recruiting@joinroot.com.

Root is on a mission to unbreak insurance by creating experiences people love at prices they can't believe. We believe that investing in world-class technology will facilitate a new class of insurance products, driving a massive positive impact on the hundreds of millions of drivers who carry auto insurance in the US. Root's Engineering team is committed to building a flexible platform on which our product designers and quantitative scientists can quickly test ideas, deploy them into production, and iterate, with the ultimate objective of a delightful customer experience coupled with effective risk management.