Life 360is hiring an AI-Native Mobile Focused Engineer — an engineer who doesn’t just use AI tools, but thinks natively in them. You’ll be central to how the Foundry team builds its products, develops its ecosystem tooling, and how we use AI for development in the future. You’ll design and build features that serve some of our most important and fastest-growing member segments: aging parents who want to stay safely connected with their families, pre-teens with wearables taking their first steps toward independence, sports teams that need real-time coordination, and school communities simplifying carpool logistics. You’ll build and evolve our modern AI-Native engineering workflows — from how we write code, to how we run standups, to how we think about team velocity. You’ll evolve the standard others follow. Mobile experience is strongly preferred (iOS or Android), though exceptional full-stack or backend engineers are also encouraged to apply. For candidates based in the US, the salary range for this position is $118,000 to $161,500 USD. For candidates based out of Canada, the salary range for this position is 136,500 to 149,500 CAD. Note: We take into consideration an individual's background and experience in determining final salary- therefore, base pay offered may vary considerably depending on geographic location, job-related knowledge, skills, and experience. The compensation package includes a wide range of medical, dental, vision, financial, and other benefits, as well as equity. What You’ll Do Design and build high-quality features integrating third party data and systems. Work with AI (Claude Code) as a first-class collaborator — your primary workflow involves orchestrating agents to create specs, generate code and tests, verify results, and perform reviews. Help define and codify AI-Native engineering practices for the Foundry team, establishing playbooks the broader org can adopt. Build across the full stack as needed — shipping polished, performant, and reliable experiences to tens of millions of users. Collaborate closely with product managers and designers to turn complex user problems into elegant, scalable engineering solutions. Contribute to architectural decisions, code reviews, and a culture of craft and continuous improvement. Participate in on-call rotation and incident response. Use agentic workflows to dramatically increase the delivery of strong outcomes — moving faster without sacrificing quality. Mentor team members and contribute to team processes, technical standards, and help evolve the team's AI-native engineering practices. Support performance, reliability, and accessibility across the features you own. What We’re Looking For 3 years of experience building high-quality, consumer-scale software products. At least 1 year of hands-on experience prompting, evaluating, and building with LL - Ms. Strong proficiency in mobile development (iOS or Android) — you know what great mobile UX feels like and how to build it. Web and backend experience (Java, Kubernetes, AWS) are valued alternatives. Deep experience with agentic workflows, prompt engineering, context window management, and MCP/function calling. A track record of using AI tooling to multiply your own output — not just as autocomplete, but as a genuine development partner. Strong communication and collaboration skills — you work well with product, design, and platform engineers. A genuine excitement for defining what it means to be AI-Native — you’re not waiting for the playbook, you want to write it. Empathy for the humans behind the product — an aging parent trying to stay independent, a parent tracking their pre-teen, a coach wrangling 20 families on game day. Bachelor’s Degree in a Technical field, or equivalent experience. AI-Native Expectations We use AI coding tools as a professional standard on this team. Here's what that means in practice: Daily use: You use AI coding assistants (we support Claude Code, Cursor, and GitHub Copilot) for real, substantive tasks: analysis, coding, refactoring, testing, navigating codebases, and documentation. Not just research or autocomplete. Judgment and ownership: AI-generated code gets the same review you'd give any PR. You are accountable for everything you ship. Velocity: We expect senior engineers who use AI well to operate with meaningful leverage — doing more with the same time, taking on problems that would otherwise require a larger team. Team leadership: You share what works. You automate prompting strategies that others can build on and help teammates earlier in their AI workflow adoption get up to speed. Continuous learning: The tooling is changing fast. You stay current and bring recommendations to the team when something would meaningfully improve how we work.