IoT Integration & Cloud Engineer

We are looking for an IoT Integration & Cloud Engineer to be the bridge between our devices and our platform. You will define how devices talk to the cloud, work side-by-side with backend and frontend teams, and ensure telemetry, alerts, and configurations are delivered reliably and securely from the field to the customer dashboard. Key Responsibilities • Define and implement device-to-cloud protocols (MQTT, HTTPS, WebSocket) with secure transmission (TLS, certificates, token-based auth). • Design and document device provisioning, onboarding, and OTA update workflows. • Work directly with backend developers on APIs, data structures, message schemas, and device lifecycle management. • Coordinate with frontend developers so telemetry, alerts, and configurations appear correctly on the customer dashboard. • Build integration test rigs and automated scripts to validate end-to-end flows (device cloud dashboard). • Collaborate with the Hardware Engineer on device-side communication stack and payload design. • Monitor production fleets, troubleshoot connectivity and data issues, drive improvements. • Contribute to cloud-side tooling for diagnostics, remote configuration, and fleet health visibility. • Prepare integration documentation, API specs, and runbooks for support and field teams. Required Qualifications • Bachelor s or Master s degree in Computer, Electronics, or Software Engineering. • 3 6 years in IoT integration, backend, or full-stack development with connected devices. • Strong working knowledge of IoT communication protocols (MQTT, HTTP/REST, WebSocket, TCP/IP). • Solid experience with REST APIs, JSON, authentication (OAuth/JWT), and device provisioning patterns. • Proficiency in at least one backend language (Node.js, Python, or Go). • Basic understanding of frontend frameworks (React, Vue, or similar) to collaborate on device-driven UI features. • Experience with Git and Agile workflows. Preferred Qualifications • Hands-on with AWS IoT, Azure IoT Hub, or similar cloud platforms. • Experience with time-series databases (InfluxDB, TimescaleDB) or message brokers (Kafka, RabbitMQ). • Exposure to fleet management, ADAS, DMS, or industrial safety platforms. • Familiarity with edge AI devices and streaming video/telemetry pipelines. • Some embedded/firmware exposure (enough to debug device-side issues collaboratively).