Sr. Staff AI Security Engineer, AI Native Platform

About Life360

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 emergency dispatch. Life360 serves approximately 97.8 million monthly active users (MAU), as of March 31, 2026, across more than 180 countries.

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 basically family).

Life360 has more than 500 (and growing!) remote-first employees. For more information, please visit life360.com.

Life360 is a Remote-First company, which means a remote work environment will be the primary experience for all employees. All positions, unless otherwise specified, can be performed remotely (within the US) regardless of any specified location above.

We Are AI Native

We are building an AI native company where AI is an integral part of how we build and operate. AI tool usage during interviews varies by role. You may be asked to demonstrate proficiency with AI tools, discuss how you leverage AI, or complete interview exercises without AI assistance. Your Recruiter will provide clear guidance as you move through the interview process.

Undisclosed use of AI not previously discussed with or approved by your Recruiter may impact your candidacy.

About the Team

The Information Security and Technology team is responsible for keeping Life360 safe — our systems, our employees, and the tens of millions of families who trust us with their location data. That obligation is the starting point. How we meet it is what makes this team different.

We are builders. Security controls that don't get used aren't controls. Compliance programs that create friction without reducing risk aren't programs. We build things that work in production, earn adoption from engineering teams, and get better over time — and we use AI to do it at a scale a traditional team couldn't.

We're also at an inflection point. Life360 is deploying agentic systems into how we build and operate, and the security and governance implications of that are still being worked out — by us, and by the industry. The threat surface is expanding. The compliance frameworks are catching up. The people on this team aren't waiting for either.

About the Job

We are hiring a Sr. Staff AI Security Engineer to secure Life360's AI infrastructure as it takes shape. You will sit within the AI Native Platform team, reporting directly to the CISO, working alongside the engineers designing and building each layer of the platform.

This role is grounded in execution with real architectural reach. You'll drive delivery across key security domains while contributing to design decisions that shape how the platform is built. The patterns we are securing are still being defined, and part of the work is building and validating those patterns under real conditions. You’ll be active in architecture reviews, own security implementation across your domains, and build the controls that make it safe to move fast with AI. In a domain where the playbooks are still being written, part of the role is writing them. You won't be doing this alone, you'll work alongside additional security engineers and the broader team building the platform, with the expectation that this function grows as the platform does.

The data at stake has real weight. Life360's systems carry real-time location data and family relationship graphs for tens of millions of people, including children. These are crown jewels in the truest sense — irreplaceable to the families who trust us with them. Securing the AI systems that interact with this data is not a compliance exercise. It is a core obligation of the product.

The US-based salary range for this position is $209,000 to $309,000. 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

• Secure how Life360 accesses frontier models. Design, build, and iterate the access controls, policy enforcement, and authorization patterns that govern how systems interact with the frontier models they rely on.
• Build secure patterns for MCP access and tool use authorization. Build and own the controls that vets, risk-tier, and govern how we integrate with external tools and services via MCP as adoption expands across engineering teams.
• Design and build the identity and authorization model for autonomous agents: service identities, scoped credentials, and least-privilege access patterns. Define and enforce the trust boundaries that govern how agents interact across orchestration chains.
• Design and build agentic observability and adversarial defenses. Build the telemetry pipelines and behavioral monitoring that provide visibility into AI system behavior. Implement architecture-level defenses against prompt injection and related adversarial attack classes.
• Shape security for the common AI end-user platform. Lead design reviews, build access controls, data boundary enforcement, and abuse detection that keep a shared AI environment safe across users with different privilege levels.
• Secure the shared knowledge layer. Define access control and data governance for retrieval augmented and reasoning systems, ensuring AI-powered tools don't surface sensitive data to the wrong systems or users.
• Build AI supply chain integrity into the platform. Develop model provenance practices, service vetting, and dependency controls that keep the AI stack trustworthy as it grows.
• Partner with Privacy, Legal, and Data Platform to ensure the right controls are built into pipelines handling real-time location, family relationship data, and data involving minors.

What We're Looking For

• 12+ years in security engineering with depth in application security, cloud security, IAM, or detection — and a track record of building controls that earn adoption, not just approval.
• Hands on builder shipping security controls that hold up in production. You’re not an advisor but a practitioner that can define patterns that last
• Hands-on fluency with LLM and agentic systems. You've built with these tools, broken them, and shipped fixes for prompt pipelines , RAG architectures, and multi-agent orchestration from the inside.
• Solid grounding in IAM for non-human systems: service identities, OAuth, secrets management, RBAC/ABAC, and least-privilege architecture at scale.
• Experience with production telemetry and detection — defining detections and building response paths for threat surfaces without established playbooks.
• Comfort with ambiguity and in-flight builds. You're energized by figuring things out — writing first-draft standards, testing approaches, and scaling what works.
• Strong cross-functional communication and the ability to push back when it matters. You carry risk, tradeoffs, and technical decisions across engineering, product, and security leadership without losing precision — and can reshape a risky decision clearly and constructively.
• Familiarity with NIST AI RMF, OWASP LLM Top 10, and adjacent compliance environments for consumer data at scale.
• Bachelor's degree or equivalent experience in Computer Science, Information Security, or a related field.

Bonus points if you have:

• Experience with frontier model API security, tool-use authorization patterns, or access governance for AI systems at scale.
• Hands-on experience with multi-agent orchestration frameworks (LangGraph, AutoGen, CrewAI, or similar) and their trust, identity, and authorization challenges.
• Familiarity with knowledge graph architectures, vector stores, or RAG systems — and the access control and data boundary problems they introduce.
• Red teaming or adversarial testing against AI systems: prompt injection, jailbreaks, data extraction, model inversion, or supply chain attacks.
• Background in consumer technology or another domain where personal data sensitivity is a core product obligation — not just a legal requirement.
• Experience designing or reviewing security for internal enterprise AI platforms serving non-technical users.

Our Benefits

• Competitive pay and benefits
• Medical, dental, vision, life a