Senior Command and Control Software Engineer
$140,000–$220,000 year
On-site · Clarksburg, Maryland, United States
Job Summary
Senior embedded engineer to own software end-to-end on edge devices — from the real-time signal-processing pipeline up through data contracts and C2 interfaces that turn spectrum awareness into operator-facing information. Develop edge software and real-time pipelines in modern C++ for deployed NVIDIA Jetson (ARM/Linux) devices, build low-latency data flows between processing stages, integrate with radios/RF front-ends, design wire-level data formats and interface contracts (Protobuf), enable event-driven alerting and on-device telemetry, and incorporate edge ML inference (TensorRT/ONNX). Own the build/deploy workflow (CMake, Conan, Docker) and collaborate across systems, hardware, and integration teams to deliver end-to-end functionality.
Required Qualifications
- 5+ years of professional software engineering experience, with substantial time in edge, embedded, or systems-level environments
- Strong modern C++ (C++17/20) on Linux, plus Python for tooling and automation
- Experience building real-time or low-latency systems: deterministic pipelines, queuing, concurrency, and processing under throughput and timing constraints
- Demonstrated ownership of wire-level data formats, custom protocols, or packet/interface contracts (Protobuf or equivalent)
- Comfort with C++ build and dependency tooling (CMake, a package manager such as Conan) and containerized dev/deploy workflows (Docker)
- Track record of taking embedded software from bring-up through deployment on real hardware, working across firmware, host software, sensors, and integration teams
- Ability to set technical direction and own a meaningful slice of architecture on a small team
Desired Qualifications
- RF / DSP fundamentals: IQ data, spectral processing, detection, or direction finding
- Experience on NVIDIA Jetson or comparable ARM/SoC edge platforms
- Zero-copy IPC or shared-memory pub/sub frameworks (iceoryx2, DDS, or similar)
- Edge ML inference deployment (TensorRT, ONNX)
- Sensor integration and fusion (IMU, multi-rate sensor inputs)
- Background in defense, EW/SIGINT, or other mission-critical real-time systems
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