About The Team
The Devices Cloud team owns the backend services that power Life360's fleet of connected hardware — Tile trackers, Jiobit wearables, Pet GPS trackers, and emerging device categories. We manage real-time device state, high-frequency telemetry ingest, and the cloud infrastructure that translates physical-world signals into reliable, family-facing experiences. Our work sits at the intersection of hardware, firmware, mobile, and platform — and runs at a scale where correctness and reliability aren't optional.
We are an AI-Native team. AI isn't an add-on to how we work — it's how we work. We've redesigned our development workflows around AI, using it as a first-class collaborator at every stage: spec writing, code generation, test authoring, incident triage, and system design. We ship faster and go deeper because of it. We're looking for engineers who want to help define what AI-native backend development looks like for complex, hardware-connected systems.
About the Job
As a Backend Engineer II on the Devices Cloud team, you will build and improve the cloud services that power Life360's connected hardware — Tile trackers, Jiobit wearables, and emerging device categories. You own well-defined components and features across device state management, telemetry ingest, and the integration layer that connects physical hardware to family-facing experiences.
You work with growing independence. You contribute to technical designs, own smaller designs yourself, break down tasks, and deliver reliable, well-tested code with occasional guidance from senior engineers. You collaborate with firmware, mobile, platform, and data teams, and you continue to deepen your technical skills. Your work helps power experiences for tens of millions of families daily.
You are also growing as an AI-native engineer. You use AI as a first-class collaborator across coding, testing, and debugging, learn the practices that work on the team, and take full ownership of everything you ship.
What You’ll Do
- Build and maintain components and features of Devices Cloud services — telemetry ingest, state management, command/control, and data pipelines — with a focus on quality and reliability.
- Own well-defined features and smaller designs from implementation through production, breaking down tasks and delivering accurate estimates with occasional guidance.
- Use AI-native engineering practices in your daily work: AI assistants for coding, testing, refactoring, and debugging, while owning and reviewing everything you ship.
- Work with firmware, mobile, product, and platform teams to implement APIs and integrations across the hardware-software boundary.
- Contribute to cross-team efforts, and escalate risks and blockers early.
- Thoroughly test your own code to catch logic issues before integration, and learn cross-functional requirements around security and scalability.
- Follow code review best practices, give and receive constructive feedback, and learn from senior engineers.
- Translate technical specifications into high-quality code, and contribute to team documentation.
- Communicate progress clearly and surface blocking issues early to your team and manager.
- Participate in on-call rotation and contribute to incident response and post-mortems.
What We’re Looking For
- 5+ years of experience in software engineering experience building backend or cloud services.
- Experience building defined features, investigating and fixing bugs, and writing test code with growing independence.
- Working knowledge of cloud-native infrastructure (AWS: EKS, Lambda, DynamoDB, SQS, Kinesis, etc.) and a desire to deepen your distributed-systems skills.
- Hands-on experience using AI coding assistants for real engineering tasks, with the judgment to review and own what you ship.
- Solid coding and problem-solving skills, and a habit of self-testing to deliver low-defect work.
- A clear communicator who shares progress, asks insightful questions, and explains their work to peers and their manager.
- Able to work semi-independently, unblock yourself, and ask for guidance when you need it.
- Experience with high-frequency ingest systems, time-series data, and streaming platforms (Kafka, Kinesis, or similar).
- Bachelor’s Degree in a Technical field, or equivalent experience.
Nice to Have
- Experience with IoT, telematics, embedded, or firmware-adjacent systems.
- Background in SRE practices, reliability engineering, and progressive delivery.
- Familiarity with observability platforms (Prometheus, Grafana, OpenTelemetry, DataDog).
- Experience contributing to industry conversations: open-source projects, conference talks, or technical publications.
- Knowledge of hardware/firmware communication protocols (MQTT, BLE, CoAP, etc.).
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: You understand that the AI is a tool, and you are fully responsible for the correctness, performance, and security of any code or design you ship, even if it was AI-generated. You rigorously review, test, and validate all AI output.