Job Description

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 Manager

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--it's 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

10+ years in engineering, with at least 5 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
Job Types: Full-time, Permanent

Experience:

embedded/firmware/hardware: 5 years (Required) technical leadership: 3 years (Required)
Work Location: In person