Join a mission-driven team transforming public safety through real-time video analytics and automated enforcement. This role is at the forefront of moving AI capabilities from the cloud to intelligent edge devices - where speed and accuracy are critical.

The client is seeking an Engineering Leader to lead the development of next-generation Edge AI platforms, embedded firmware, and custom hardware systems. This leadership role will oversee the full technology stack - from low-level embedded software to AI acceleration hardware - to enable fast, reliable, and safety-critical decision-making in real-world environments.

This is more than a technical role - its about building high-performing teams, shaping the future of intelligent edge systems, and delivering real-world impact.

Key Responsibilities :

- Team Leadership : Build and lead a multidisciplinary engineering team across embedded software, edge AI, and hardware.

- Technology Roadmap : Define and drive the vision and roadmap for embedded computing and edge AI hardware platforms.

- Architecture & Design : Make high-level architectural decisions for firmware, embedded AI pipelines, and purpose-built hardware, with a focus on performance and power efficiency.

- Edge AI Deployment : Enable cloud-trained AI models to operate efficiently on edge devices with limited resources.

- Hardware & Firmware Development : Manage integration across SDKs, HALs, and toolchains for AI chips like NVIDIA Jetson, Intel Movidius, Hailo, and ARM NPUs.

- Performance & Reliability : Deliver robust, fault-tolerant systems that meet real-time constraints, especially in mobile/vehicle-mounted applications.

- Cross-Functional Collaboration : Work closely with AI/ML teams, product management, and executive leadership to align engineering efforts with business goals.

- Culture Building : Foster a culture of innovation, technical excellence, and accountability within the embedded and edge computing teams.

Preferred Qualifications :

- 20+ years in engineering, with at least 10 years in embedded/firmware/hardware roles and 3+ years in technical leadership.

- Experience building and scaling engineering teams in embedded systems or edge AI domains.

- Strong grasp of deploying deep learning models on edge devices (quantization, pruning, etc.).

- Familiarity with edge AI toolchains : TensorRT, OpenVINO, TFLite, HailoRT, etc.

- Proficiency in firmware and embedded software development using C/C++, Python, and tools like Yocto.

- Experience with multi-camera systems, video/image processing pipelines (GStreamer, OpenCV, FFmpeg).

- Understanding of real-time systems and low-power hardware design.

- Excellent communication and leadership skills.

- Degree in Electrical/Computer Engineering or related field.

Why Join ?

- Lead innovation at the edge of AI, firmware, and custom hardware.

- Shape the development of distributed AI systems that have a direct impact on safety.

- Work on fast, life-saving technologies deployed in real-world environments.

- Collaborate globally with top engineers and AI experts