Staff Software Engineer, AI Systems

Root Inc. is an insurance technology company using advanced technology to create improved auto insurance experiences and products. The Staff Software Engineer, AI Systems will set technical direction for AI-enabled systems, lead cross-team initiatives, and connect user workflows with reliable, secure, and scalable AI platforms. The role also involves making architecture and operational tradeoffs, aligning stakeholders, establishing performance feedback loops, and mentoring engineers and technical leaders.

Responsibilities:

• Set a 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 sound 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 that show whether AI capabilities are dependable and whether adoption improves how Root works
• Anticipate emerging constraints, shape technical investments, and multiply your impact by mentoring engineers and technical leaders

Requirements:

• 7+ years of software engineering experience and 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: you can 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, ideally including AWS, Terraform, and secure software delivery
• 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