Senior Engineer, C++ Software - Edge Systems (R5190)

Shield AI is seeking a C++ Software Engineer, Edge Systems to build mission-critical edge software for unmanned systems operating in demanding real-world environments. This role sits within the systems team, where software meets hardware. You will work across sensors, edge compute, imaging pipelines, mission systems, and autonomy.

You will develop production C++ software for Linux-based edge compute platforms, including NVIDIA Jetson-class systems and other ARM-based embedded platforms. You will work on sensor integration, hardware-facing applications, calibration tools, diagnostics, and mission-system interfaces. This is a hands-on role for an engineer with proven experience delivering reliable software that runs on real systems, not just prototypes.

You will work closely with systems, hardware, autonomy, AI, product, and test engineers to turn advanced capability into integrated, tested, fieldable software.

Design, develop, test, and maintain production C++ software for edge systems, imaging systems, mission applications, developer tooling, and automated test infrastructure.

Build Linux-based applications for NVIDIA, ARM, and other embedded compute platforms connected to real sensors, payloads, peripheral hardware, and mission systems.

Integrate camera inputs such as RGB, NIR, and thermal, alongside GPS, IMU, communications, and other sensor or peripheral inputs using interfaces such as MIPI CSI, GMSL, Ethernet, serial, or similar hardware-facing protocols.

Develop calibration, synchronisation, data capture, diagnostics, device inspection, and system configuration tools for multi-sensor and mission-system environments.

Optimise software for latency, frame rate, throughput, reliability, power use, and thermal performance on constrained edge compute platforms.

Debug issues across software, hardware, operating systems, networking, sensors, timing, compute, and deployment environments.

Collaborate across systems, hardware, autonomy, AI, product, and test teams to deliver integrated capability.

Own technical outcomes from ambiguous requirements through implementation, integration, verification, and delivery.

Degree in Computer Science, Software Engineering, Electrical Engineering, Robotics, a related technical field, or equivalent real-world engineering experience.

Proven commercial or production C++ development experience, including designing, implementing, debugging, and maintaining non-trivial software systems.

Demonstrated experience building software that interfaces with real hardware, sensors, embedded devices, robotics, vehicles, imaging systems, networks, or other operational platforms.

Practical experience developing and debugging software on Linux-based systems.

Experience working with edge compute, embedded compute, ARM-based platforms, NVIDIA platforms, or comparable hardware-constrained environments.

Strong software engineering fundamentals, including concurrency, interfaces, memory management, data structures, algorithms, testing, and version control.

Proven ability to debug complex issues across software, hardware, operating systems, networking, timing, and integration boundaries.

Experience owning technical work from incomplete requirements through design, implementation, integration, verification, and delivery.

Ability to collaborate effectively with cross-functional engineering teams, including systems, hardware, test, autonomy, AI, or product stakeholders.

Runtime-critical, multi-threaded, or performance-sensitive C++ software for real-time or near-real-time systems.

Imaging, video, or sensor pipelines, including camera integration, ISP tuning, high-throughput image processing, GStreamer, FFmpeg, or similar technologies.

Hardware-accelerated processing on embedded or edge platforms, including NVIDIA Jetson, Qualcomm-based platforms, embedded AI accelerators, GPU-accelerated video or compute pipelines, or similar systems.

Integration of peripheral hardware such as RGB, NIR, and thermal cameras, GPS, IMU, GPU, or vehicle-interface systems.

Robotics, aerospace, defence, autonomy, unmanned systems, automotive, or other mission-critical domains.

Systems architecture, including interface design, system decomposition, testability, reliability, and maintainability.

Low-level Linux, device interfaces, vendor SDKs, driver-adjacent debugging, NixOS, edge AI/ML inference, or related Linux-based deployment environments.

Automated build, CI/CD, simulation, software-in-the-loop, hardware-in-the-loop, system test, containerised deployment, or deployment tooling.