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Embedded Systems Manager

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Singapore beBeeEmbedded Full time $125,000 - $175,000
Senior Firmware Engineering ManagerFirmware leadership roleJob Description

The goal of this position is to lead the firmware development lifecycle from architecture and design to implementation, validation, and deployment. As a Senior Firmware Engineer, you will take on the role of Team Lead for our firmware group, blending hands-on embedded firmware development with technical leadership and strategic oversight.

This senior-level position involves leading a dedicated team in the design, development, and optimization of firmware for cutting-edge cybersecure hardware products. Working closely with cross-functional teams, including hardware, FPGA, and cybersecurity engineers, you will help define and deliver secure, high-performance, real-time firmware systems on ARM and FPGA-based platforms.

Main Responsibilities:
  • Lead the firmware development lifecycle, guiding junior engineers, performing technical reviews, and helping grow team capabilities.
  • Design, develop, and maintain low-level firmware and device drivers for ARM and FPGA-based embedded platforms.
  • Collaborate with hardware and FPGA engineers to define system architecture and interface layers.
  • Implement cybersecurity measures such as encryption, secure key storage, and tamper detection in firmware.
  • Oversee firmware testing infrastructure, including unit testing, integration testing, and CI support.
Requirements:
  • Bachelor's or Master's degree in Electrical Engineering, Computer Engineering, Computer Science, or related discipline.
  • 7+ years of experience in firmware or embedded software development, with at least 2 years in a technical leadership role.
  • Proficient in C/C++, with additional experience in Python for scripting and testing.
  • Strong experience with ARM architectures (e.g., Cortex-A/M) and SoC platforms.
  • Expertise in firmware-hardware interaction, device drivers, memory-mapped I/O, and BSPs.
Preferred Qualifications:
  • Experience with secure embedded systems: secure boot, encryption, key management.
  • Knowledge of cybersecurity principles, threat models, and countermeasures.
  • Familiarity with AI/ML deployment on embedded platforms (e.g., anomaly detection via lightweight neural networks).