Backend Engineer (AI-Native) - Vertical Experiences (Devices Cloud) at Life360

As a Backend Engineer on the Vertical Experiences (Devices Cloud) team, you’ll build and operate the cloud services that power Life360’s connected devices. This role sits at the intersection of hardware, firmware, and mobile, translating real-world device signals into reliable, scalable backend systems. You’ll work on high-throughput, low-latency services that manage device state, ingest telemetry, and enable new device-driven features for millions of members worldwide. The work is hands-on, systems-oriented, and designed for engineers who enjoy solving messy, real-world problems at scale.

You don’t just use AI tools. You think natively in them. Your primary workflow involves orchestrating agents to create specs, generate code and tests, verify results, and perform reviews. You’ll help establish and evolve AI-native engineering practices for the Vertical Experiences team while delivering features that ship to production weekly.

What You’ll Do

• Design, build, and maintain backend services that support device connectivity, telemetry ingest, health monitoring, and command/control operations.
• Collaborate with firmware, mobile, and product teams to define APIs and workflows for device features.
• Deliver scalable, resilient systems in a microservices environment running on AWS (EKS, Lambda, DynamoDB, SQS, etc.).
• Build and own data pipelines for high-throughput streams using Kafka or similar streaming tech.
• Instrument services for observability, reliability, and SLO compliance.
• Participate in on-call rotations and live incident response.
• Write clean, testable, performant code and help improve CI/CD and automation.
• Orchestrate AI coding agents daily for spec writing, code generation, test authoring, incident triage, PR review, and system design.

What We’re Looking For

• A Bachelor’s in Computer Science or equivalent experience.
• 5+ years experience building backend services in Java, Go, Python, or similar languages.
• Experience with microservices architecture, RESTful API design, and distributed systems.
• Strong skills with cloud infrastructure (AWS preferred), container orchestration, and deployments.
• Experience with databases (relational and/or NoSQL), caching layers, and event/streaming systems.
• Comfortable collaborating across teams and articulating technical tradeoffs.
• Hands-on agentic AI workflow experience.

Nice-to-Have

• Experience with IoT or telematics systems.
• Familiarity with Kafka, Kinesis, or other streaming platforms.
• Experience with high-frequency ingest systems and time-series data. A background with observability tooling (Prometheus, Grafana, OpenTelemetry).
• Knowledge of SRE practices and automated testing frameworks.

AI-Native Expectations

We use AI coding tools as a professional standard on this team. Here’s what that means in practice:

• Daily use: You use AI coding assistants (we support Claude Code, Cursor, and GitHub Copilot) for real, substantive tasks: analysis, coding, refactoring, testing, navigating codebases, and documentation. Not just research or autocomplete.
• Judgment and ownership: AI-generated code gets the same review you’d give any PR. You are accountable for everything you ship.
• Velocity: We expect senior engineers who use AI well to operate with meaningful leverage — doing more with the same time, taking on problems that would otherwise require a larger team.
• Team leadership: You share what works. You automate prompting strategies that others can build on.
• Continuous learning: The tooling is changing fast. You stay current and bring recommendations to the team.