Staff Software Engineer, AI Systems

Root Insurance

77d•$188,800 - $265,000•Remote

About The Position

As a Staff Software Engineer focused on AI, you will help build trustworthy, useful AI capabilities across Root. You will set technical direction, lead work across teams, and connect real-world user needs to the platforms and practices that support them. The role may emphasize foundational platform engineering or hands-on enablement and adoption, depending on your strengths and organizational needs. The work spans two connected teams: AI Platform, which builds shared infrastructure, tooling, and operating patterns for reliable and secure AI; and AI Enablement Squad, which partners with teams to apply AI in their workflows and turns those learnings into reusable capabilities. Your impact will extend beyond either team.

Requirements

7+ years of software engineering experience.
3+ years leading software teams or major technical initiatives.
A record of setting technical direction and delivering results across multiple teams or a meaningful engineering domain.
Strong systems and product judgment, including the ability to frame ambiguous problems, evaluate tradeoffs, and turn learning into reusable capabilities.
Experience with AI/LLM technologies and application patterns, with sound judgment about responsible, scalable use.
Depth in cloud/platform architecture and production operations; AWS, Terraform, and secure software delivery are noted as ideal experience.
Depth in hands-on AI enablement, user-centered problem discovery, and translating experiments into products or operating models.
Ability to drive cross-team decisions, communicate complex ideas to senior technical and non-technical leaders, and develop engineers beyond your immediate team.
Candidates must be on camera for virtual interviews; this is a standard requirement to proceed in the interview process.

Nice To Haves

Experience with AWS, Terraform, and secure software delivery.

Responsibilities

Set multi-quarter technical direction for how Root builds, adopts, and improves AI-enabled systems, balancing immediate opportunities with durable investments.
Lead cross-team initiatives from ambiguous problem framing through architecture, implementation, and measurable outcomes.
Connect real user workflows and experiments to shared services, platform strategy, and scalable ways of working rather than one-off solutions.
Make tradeoffs across security, responsible use, reliability, observability, cost, usability, and long-term maintainability.
Align engineering and business leaders on priorities and decisions; unblock work across product engineering, data, security, infrastructure, and other partners.
Establish feedback loops and measures to assess whether AI capabilities are dependable and whether adoption improves how Root works.
Anticipate emerging constraints, shape technical investments, and multiply impact by mentoring engineers and technical leaders.