Staff Backend Engineer (AI Native), Family AI Lab

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. Life360 serves approximately 97.8 million monthly active users (MAU) across more than 180 countries.

Life360 is a Remote-First company. All positions, unless otherwise specified, can be performed remotely (within the US and Canada).

About The Team
The AI Lab is a small, founder-led team operating like a zero-to-one startup inside Life360, building the company's next chapter. Our mission is to transform Life360 from the app you open to find your family into an intelligent operating system families rely on daily. We design and build an AI-powered layer on top of our family graph, leveraging our core location technologies and global 100 million-user base to proactively surface what matters across location, schedules, and everyday life.

About the Job
Your role is owning how Life360's deterministic backend (location data, the family graph, behavioral signals, user insights) pairs with the probabilistic world of LLMs. You decide how those two sides talk to each other, and you make sure the seams don't show.

You own the inference pipeline end to end: model selection, serving infrastructure, evaluation loops, prompt and context strategy, and the cloud services that keep it all running in production. You make the tradeoffs between latency, cost, and quality. You build the eval harness that tells us whether the system is actually getting better, not just feeling different. If you do this job right, the product feels seamless to users, the data stays safe, and inference costs don't run away from us.

You are a cloud engineer who is deeply fluent in how AI systems actually work in production.

Responsibilities

• Architect inference pipelines that turn Life360 data into a context layer LLMs can reason over
• Select models and hosting infrastructure: self-hosted, API-based, fine-tuned, or prompt-engineered
• Build serving infrastructure with clear latency budgets, caching, and graceful degradation
• Establish evaluation frameworks that distinguish actual product improvements from vibes-based iteration
• Manage cost models tracking spend across users, features, and families
• Define data architecture decisions: persistence, summarization, and LLM accessibility
• Establish safety and privacy controls at the infrastructure layer

Required Qualifications

• Substantial production experience building and operating AI systems at scale
• Fluency in modern LLM serving frameworks (vLLM, TGI, SGLang, hosted APIs)
• Hands-on experience building evaluation harnesses
• Cloud systems architecture and reliability expertise
• Strong cost optimization instincts
• Daily proficiency with AI tools (Claude Code, Cursor, or equivalent)
• Native thinking in agentic workflows, prompt engineering, context window management
• Comfort with incomplete specifications
• Excellent technical written communication
• Preferred: agent systems, retrieval pipelines, long-context personalization, or privacy architecture experience

Salary
For candidates based in the US, the salary range for this position is $190,000 to $280,000 USD.

Benefits

• 100% employer-paid medical/dental/vision for US employees
• 401(k) matching (US)
• Flexible PTO plus 12 company days off
• Learning & development programs
• Remote equipment support
• Free Life360 Platinum Membership