Senior Backend Engineer II - AI-Native, Devices Cloud

Life360 is a company dedicated to keeping people close to their loved ones through its mobile app and tracking devices. As a Senior Backend Engineer on the Devices Cloud team, you will build and operate cloud services that support connected devices, leveraging AI to enhance development workflows and deliver reliable backend systems.

Responsibilities:

• Design, build, and maintain backend services for device connectivity, telemetry ingest, health monitoring, and command/control operations — using AI (Claude Code) as a first-class collaborator in your daily development workflow
• Use agentic workflows to dramatically increase delivery velocity without sacrificing quality: from generating service scaffolding, to writing and validating test coverage, to triage and root cause analysis during incidents
• Help define and codify AI-native engineering practices for the Devices Cloud team — establishing patterns the broader org can adopt
• Collaborate with firmware, mobile, and product teams to define APIs and workflows for device-driven features
• Build and own data pipelines for high-throughput telemetry streams using Kafka or similar streaming technologies
• Deliver scalable, resilient microservices on AWS (EKS, Lambda, DynamoDB, SQS, etc.)
• Instrument services for observability, reliability, and SLO compliance
• Participate in on-call rotation and live incident response
• Write clean, testable, performant code; contribute to CI/CD automation and improve team-wide engineering standards
• Mentor teammates and help evolve the team's AI-native engineering culture

Requirements:

• 5+ years of experience building and operating high-quality backend services in Java, Go, Python, or similar languages
• Hands-on experience prompting, evaluating, and building with LLMs — not just autocomplete, but as a genuine development partner
• Deep experience with agentic workflows, prompt engineering, context window management, and MCP/function calling
• A track record of using AI tooling to multiply your own output — faster specs, better test coverage, cleaner code, faster debugging
• Strong experience with microservices architecture, RESTful API design, and distributed systems
• Solid skills with cloud infrastructure (AWS preferred), container orchestration, and production deployments
• Experience with databases (relational and/or NoSQL), caching, and event/streaming systems
• Ability to collaborate across teams and articulate technical tradeoffs clearly
• A genuine drive to define what AI-native looks like for complex, hardware-connected systems — you're not waiting for the playbook, you want to write it
• Experience with IoT, telematics, or embedded/hardware-adjacent systems
• Familiarity with Kafka, Kinesis, or other high-throughput streaming platforms
• Experience with high-frequency ingest systems and time-series data
• Background with observability tooling (Prometheus, Grafana, OpenTelemetry, DataDog)
• Knowledge of SRE practices and automated testing frameworks