Fleet Reliability Engineer - Intuitive AI (Surrey)

Company Description Intuitive AI is dedicated to addressing the global waste crisis by creating innovative solutions that make waste management more effective and impactful. Our mission is to inspire changes in behavior and foster sustainability through advanced technology and user-friendly systems. With a focus on environmental stewardship, we aim to empower individuals and organizations to make responsible waste disposal choices. At Intuitive AI, we believe in making a lasting impact and creating a cleaner planet for future generations. Location: Hybrid - Vancouver office The Role We're hiring a Fleet Reliability Engineer to help us keep that fleet healthy, observable, and improving. You'll work directly alongside our Senior Engineers to maintain, monitor, and scale the thousands of Oscar Sort and Pixel units deployed worldwide - catching issues before they happen, automating the boring stuff, and shipping the systems that let a small team operate a fleet far bigger than it has any right to. You'll have a senior engineer in your corner from day one, and real ownership from week one. The work is hands‑on, the feedback loop is rapid, and what you build will be running on devices in real customer sites within days. What You’ll Work On - Diagnosing and resolving issues on Linux-based edge devices in the field; logs, crashes, network drops, hardware quirks - Building and maintaining our fleet management, monitoring, and alerting systems - Owning OTA updates and release rollouts - staged deployments, rollbacks, canary fleets - Writing scripts and tooling to automate diagnostics, remediation, and routine maintenance - Improving system reliability - driving down recurring issue classes, reducing manual support load, raising fleet uptime - Supporting edge AI model deployments alongside our ML team - Partnering with Customer Success when client‑facing issues need engineering depth What We’re Looking For Required - 2–4 years working with Linux systems in a production or fleet context - Robust command line fluency and systems‑level debugging chops - Solid scripting in Python and Bash - Networking fundamentals - SSH, TCP/IP, firewalls, VPNs, basic troubleshooting - Experience with monitoring or observability tooling (Prometheus, Grafana, Datadog, Loki, or similar) - Hands‑on experience with embedded Linux, IoT, or edge devices — this is the core of the role, not a side interest - Experience with OTA / fleet update systems (Mender, RAUC, balena, AWS IoT Greengrass, or similar) - Comfortable with Docker and containerized workflows - A genuine problem‑solving instinct - you don't stop at the symptom Nice to Have - Cloud infrastructure (AWS preferred) - CI/CD pipelines and infrastructure‑as‑code - Hands‑on hardware experience (replacing components, debugging physical units remotely) - Experience operating fleets at thousands‑of‑devices scale Who You Are - Curious, hands‑on, and allergic to "we've always done it that way" - Comfortable owning a problem end‑to‑end, from the log line to the fix to the postmortem - Detail‑oriented - you trust the data, not the vibe - Energized by real‑world AI systems and devices people actually touch - Genuinely interested in why something broke, not just getting it back up Why Join - Real fleet, real customers, real impact - every change you make ships to devices in the field - Direct mentorship from senior engineers, no layers between you and the systems - High ownership in a small team where your work is visible end‑to‑end Salary Range: $70k-$80k #J-18808-Ljbffr Apply on Kit Job: kitjob.ca/job/2pe9mt