Title: Senior IoT Engineer
Company Name: Energy+ Electric & Electronics Pvt. Ltd.
Vacancy: 02
Age: 30 to 40 years
Job Location: Dhaka
Salary: Negotiable
Experience:
● Experience: 5 to 7 years of hands-on experience in IoT engineering, embedded systems, and hardware-software integration.
● Programming Languages: Expert proficiency in C and C++ for embedded systems. Strong knowledge of Python for scripting, testing, and edge computing tasks.
● Embedded Systems: Deep experience with RTOS (FreeRTOS, Zephyr) and bare-metal programming across various architectures (ARM, ESP, STM32).
● IoT Protocols: Mastery of messaging protocols like MQTT and CoAP, and wireless stacks including LoRaWAN, BLE, and Cellular IoT.
● Hardware Knowledge: Strong ability to read schematics, use oscilloscopes/logic analyzers, and perform component-level debugging. Familiarity with serial interfaces (I2C, SPI, UART, RS-485/Modbus).
● Problem Solving: Proven ability to diagnose and solve complex issues in constrained environments (power, memory, bandwidth).
● End-to-End System Architecture: Design robust and scalable IoT architectures, from sensor selection and edge node deployment to gateway communication and cloud data ingestion.
● Firmware Engineering: Write, debug, and optimize low-level firmware for microcontrollers (MCUs) and microprocessors (MPUs) using C/C++, focusing on power efficiency, memory management, and OTA (Over-The-Air) updates.
● Hardware Integration & Prototyping: Lead the integration of various sensors, actuators, and electronic components (e.g., ESP32, ARM Cortex, custom PCBs). Oversee schematic design, PCB layout, and hardware prototyping.
● Connectivity & Protocols: Implement and manage diverse communication protocols. You will architect networks using local protocols (BLE, Zigbee, Wi-Fi), Long-Range protocols (LoRaWAN, NB-IoT, Cellular 4G/5G), and application-layer protocols (MQTT, CoAP, HTTP).
● Edge Computing & AI Integration: Deploy edge processing solutions to minimize latency and bandwidth. Integrate lightweight machine learning or computer vision models onto edge devices (e.g., NVIDIA Jetson series or Edge TPUs).
● Security & Compliance: Implement hardware-level security, secure boot, TLS/SSL encryption, and secure provisioning to ensure the integrity of the IoT ecosystem from device to cloud.
● Deployment & Field Testing: Lead field testing, industrial site deployments, and hardware validation. Troubleshoot complex hardware-software integration issues in real-world environments.
● Mentorship: Guide junior embedded engineers and collaborate cross-functionally with software, mechanical, and product teams to deliver cohesive solutions.
As per company policy.