Senior Staff AI Security Engineer, Life360

• 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
• We encourage people of all backgrounds to apply. We believe that a diversity of perspectives and experiences create a foundation for the best ideas. Come join us in building something meaningful. Even if you don't meet 100% of the below qualifications, you should still seriously consider applying!

Desirable

• 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
• 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