[Hiring] Principal Agentic Engineer @Life360

Role Description

We're hiring a Principal-level Agentic Engineer to hold the system view across AI Platforms, AI DevX, and Agentic PDLC — and to give the unowned middle ground between them an owner. This is not a coordination role. You'll have clear, end-to-end ownership of a defined set of cross-cutting problems, not an open-ended advisory brief. It's an architecture-and-build role for someone who can define what an "agent" is as a reusable unit at Life360, set the standards that make agents safe and evaluable, build an ecosystem that supports our agents, and then help each team build to that architecture. In addition, this role will craft the vision for how our broad agent ecosystem will evolve into the future.

The role operates at two altitudes, and needs to be genuinely strong at both:

• Strategic: set the technical vision for Life360's AI-Native developer ecosystem — the architecture that lets AI Platforms, AI DevX, and Agentic PDLC build against shared primitives instead of re-solving the same problems three times.
• Tactical: get into the core components yourself — agent execution frameworks, context and retrieval systems, eval harnesses, identity and authZ for unattended agents — and ship the parts that are too foundational to leave to any one team, or that no team currently owns.

You'll partner closely with the AI Platforms, AI Dev Tooling, Agentic PDLC, and our Product leadership (as their technical counterpart), but you won't report through any single one of them — your mandate is the seams between all of them.

Qualifications

• 12+ years of engineering experience, including deep platform or systems architecture work at consumer scale (50M+ MAU or equivalent preferred).
• Demonstrated experience architecting agentic systems in production — not just using AI coding tools, but designing the frameworks, identity models, and eval infrastructure that other agents run on.
• Direct experience with non-human identity, service-account, or agent authZ models — or a clear, well-reasoned point of view on how to build one.
• Experience designing and consuming structured interfaces for AI systems (MCP-style tool definitions, JSON Schema, OpenAPI) and building for tool-calling and contract-first agent development.
• A track record of building eval and regression frameworks for AI systems — promotion gates, scoring, and CI integration — not just running evals ad hoc.
• Strong architectural instincts across multiple services and teams, with the judgment to know which problems deserve a shared platform investment and which don't.
• Fluency in AI economics — token cost as a design constraint, progressive retrieval, and the tradeoffs between centralizing and forking model usage.
• A track record of driving technical direction across teams you don't manage — through documentation, prototypes, and demonstrated results rather than mandates.
• Excellent written communication: architecture decision records, standards, and playbooks precise enough for other engineers (and their agents) to build against directly.

Requirements

• Experience building or operating an agent orchestration or deployment platform, or an MCP-style connector gateway.
• Background in ML infrastructure, model observability, or production AI systems at a company that has been through a comparable AI-native transformation.
• Experience with mobile engineering (iOS/Android) or high-throughput cloud systems, and how agent architecture needs to flex across both.

Benefits

• Medical, dental, vision, life and disability insurance plans (100% paid for employees)
• Paid parental leave
• 401(k) plan with company matching program
• Mental Wellness Program & Employee Assistance Program (EAP) for mental well-being
• Generous time off: flexible PTO, companywide holidays throughout the year plus summer and winter shutdowns
• Learning & Development programs
• Equipment, tools, and reimbursement support for a productive remote environment
• Free Life360 Platinum Membership and Tile trackers