About the Job
Life360’s mission is to keep people close to the ones they love. Our category-leading mobile app, Tile tracking devices, and Pet GPS tracker empower members to protect the people, pets, and things they care about most with a range of services, including location sharing, safe driver reports, and crash detection with...
Life360 delivers peace of mind and enhances everyday family life with seamless coordination for all the moments that matter, big and small. By continuing to innovate and deliver for our customers, we have become a household name and the must-have mobile-based membership for families (and those friends who are basica...
Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.
Key Responsibilities
Set the direction for the AI Platforms team, with a clear roadmap that balances today's internal needs with where the product is going
Lead and scale the team to full capacity by strategically hiring and continuing to develop current team members.
Build and evolve the shared AI platform: model access and routing, agent runtime, MCP integrations, evals, agent identity, and cost controls
Define and own our AI end-user platforms, enabling a multiplayer ecosystem working side by side with agents
Partner with core teams to evolve our Agentic PDLC, including the tools, environments, review practices, and workflows through which AI agents help plan, write, test, review, and ship code
Extend the platform from internal productivity to the product, defining how product teams access, run, and monitor AI inference and AI-powered features in production at member scale
Drive adoption by making the right way the easy way: paved paths, reusable skills and components, champions, and enablement that engineers choose to use
Partner with Security, Privacy, and Legal to build data handling, auditability, and safeguards into the platform from day one, with the trust our members expect from a family safety company
Define and report outcomes that matter, such as adoption, quality, cost per outcome, and time to ship, rather than usage counts
Stay close to the work: review designs, unblock teams, and make build-versus-buy calls as the model and tooling landscape change
Required Skills & Abilities
10+ years of engineering experience
5+ years experience leading engineering teams that build platforms or infrastructure used by other engineers
Experience building and operating production AI systems, such as agentic workflows, large language model (LLM) integrations, retrieval, and evaluation
Working knowledge of MCP and agent orchestration, including how agents connect to internal systems with appropriate controls
Familiarity with AI inference in production, including serving, latency, reliability, provider management, and cost
Experience driving the adoption of new engineering practices across a large engineering organization through influence, without becoming the bottleneck
Hands-on technical judgment: comfortable reviewing architecture, setting technical direction, and staying close to implementation
Comfort working where the platform, the operating model, and the product use cases are all taking shape at once, and a clear communicator with both executives and engineers
Nice to have: experience with consumer-scale mobile products or privacy-sensitive data
Qualifications
Experience:
5 years experience
