Principal Agentic Engineer, AI Ecosystem

Life360

9h • $247,000 - $363,000 • Remote

About The Position

Life360 is hiring a Principal-level Agentic Engineer to own cross-cutting architecture and implementation across its AI Platforms, AI Dev Tooling (AI DevX), and Agentic PDLC teams. The role has end-to-end ownership of defined problems in the shared space between these teams and is responsible for establishing reusable agent primitives, safety and evaluation standards, and the ecosystem that supports agents. It will also shape the future vision for Life360’s agent ecosystem.

The role combines strategic architecture with hands-on engineering. Strategically, it sets the technical vision for an AI-native developer ecosystem in which the teams build on shared primitives. Tactically, it works directly on foundational components such as agent execution frameworks, context and retrieval systems, evaluation harnesses, and identity and authorization for unattended agents. The engineer will ship production code, validate architecture against live use cases, and help teams build to shared standards.

The role partners with AI Platforms, AI Dev Tooling, Agentic PDLC, and Product leadership, but does not report through any one of those teams. The position is US-based and remote-first. The stated US salary range is $247,000–$363,000; final base pay may vary with background, job-related knowledge, skills, experience, and geographic tier. Total compensation includes Restricted Stock Units (RSUs) and a benefits package.

Requirements

• 12+ years of engineering experience.
• Deep platform or systems architecture experience; experience at consumer scale of 50M+ monthly active users or equivalent is preferred.
• Demonstrated experience architecting agentic systems in production, including frameworks, identity models, and evaluation infrastructure used by other agents.
• Direct experience with non-human identity, service-account, or agent authorization models, or a clear, well-reasoned point of view on how to build one.
• Experience designing and consuming structured interfaces for AI systems, such as MCP-style tool definitions, JSON Schema, or OpenAPI, and building for tool-calling and contract-first agent development.
• A track record of building evaluation and regression frameworks for AI systems, including promotion gates, scoring, and CI integration.
• Strong architectural judgment across multiple services and teams, including when to make shared platform investments.
• Fluency in AI economics, including token cost as a design constraint, progressive retrieval, and tradeoffs between centralizing and forking model usage.
• A track record of driving technical direction across teams without direct management authority, through documentation, prototypes, and demonstrated results.
• Excellent written communication, including producing precise architecture decision records, standards, and playbooks for engineers and agents.

Nice To Haves

• 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 undergone a comparable AI-native transformation.
• Experience with mobile engineering (iOS/Android) or high-throughput cloud systems, and understanding of how agent architecture must adapt to both.

Responsibilities

• Hold the system view across AI Platforms, AI DevX, and Agentic PDLC so investments compose rather than conflict.
• Drive build-versus-buy decisions for PDLC-critical agents and ecosystem-wide capabilities.
• Build the shared agent ecosystem, including execution frameworks, context and retrieval systems, and telemetry that treats token spend as a design constraint.
• Define a reusable agent unit, its interfaces, and standards for human-in-the-loop requirements, blast-radius policy, evaluation, and promotion gates, in partnership with AI Platforms.
• Design non-human identity and agent authorization models for scheduled and unattended agents across teams.
• Establish shared evaluation and regression infrastructure, including frameworks, CI hooks, and result storage.
• Ship production code for high-leverage foundational components and prototype or de-risk difficult technical work before teams commit engineering time.
• Work with live initiatives, such as the on-call investigation agent, to validate architecture under real usage and economic constraints.
• Mentor Agentic Engineers and Staff engineers across the three teams on agent architecture, context engineering, and evaluation rigor.
• Write architecture decision records, standards, and playbooks that enable the teams to build independently against a coherent technical direction.
• Represent a technical point of view in build-versus-buy and roadmap discussions without formal authority over the teams.

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 and Employee Assistance Program (EAP).
• Flexible PTO, companywide holidays, and summer and winter shutdowns.
• Learning and Development programs.
• Equipment, tools, and reimbursement support for a productive remote environment.
• Free Life360 Platinum Membership and Tile trackers.
• Equity compensation in the form of Restricted Stock Units (RSUs).

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: No Education Listed