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The Greater Change

IoT & Wearables Integration Engineer - Smart Home & Agentic AI

Backend EngineeringPosted on Nov 7
Full-timeDubai - United Arab Emirates

About the Job

Requirements

  • At least 4 years of hands-on engineering experience in IoT, wearable data integration, or ambient computing ecosystems.
  • Deep understanding of REST APIs, webhooks, GraphQL, and SDKs for Apple HealthKit, Google Health Connect, Oura, Whoop, and similar health platforms.
  • Practical experience with room-level tracking technologies, including Bluetooth Low Energy triangulation, Angle-of-Arrival, RSSI filtering, Wi-Fi Channel State Information sensing or Ultra-Wideband spatial awareness, Passive Infrared sensors, millimeter-wave radar, and RFID tracking systems.
  • Strong grasp of low-power wireless protocols, including Bluetooth Low Energy, Zigbee, Z-Wave, Thread, and Matter, and real-time data transport using MQTT, WebSockets, and gRPC.
  • Proficiency in Python, C/C++, Rust, or TypeScript/Node.js.
  • Experience with local edge gateways such as Raspberry Pi, NVIDIA Jetson, ESP32, or Home Assistant, and computer vision frameworks such as OpenCV and MediaPipe.

Responsibilities

  • Design and maintain robust API/SDK integrations with wearable platforms, including Apple HealthKit, Google Health Connect, Oura Cloud, Whoop, and unified health APIs such as Terra API and Human API.
  • Process, normalize, and ingest continuous biometric data, including HRV, skin temperature, sleep stages, stress levels, recovery scores, and blood oxygen, into the real-time agentic context engine.
  • Implement data anonymization, local-first storage paradigms, and strict compliance standards such as HIPAA and GDPR to safeguard sensitive health metrics.
  • Architect ambient presence systems using Bluetooth Low Energy RSSI/Angle-of-Arrival triangulation, Wi-Fi Channel State Information sensing, and Ultra-Wideband for hyper-local room tracking.
  • Integrate occupancy sensors, room-level RFID tracking, and optical/thermal sensors to identify user presence without requiring active user input.
  • Coordinate with hardware and vision teams to integrate edge computer vision platforms, including face scanners, OpenCV, and depth cameras, for identity and mood recognition.
  • Translate biological signals such as elevated stress, deep sleep onset, and low recovery into actionable triggers and context payloads for home automation agents via MQTT, WebSockets, or gRPC.
  • Build edge-friendly data reduction routines, including noise filtering, offline buffering, and moving-baseline calculations using Kalman filters, to prevent signal overload on downstream home AI models.

Desired Qualifications

  • Prior experience developing context engines or state machines for smart home systems, such as Home Assistant, the Matter standard, or custom AI agents.
  • Familiarity with biometric signal processing, anomaly detection, or circadian rhythm modelling.
  • A strong background in local-first architecture and end-to-end data encryption for privacy-preserving IoT systems.

About the Company

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