We're building autonomous aerial systems that think onboard — the future of the unmanned ecosystem. As our UAS Systems Architect for Edge AI, you'll own the end-to-end technical architecture of those systems, from first principles through fielded capability. This is a senior individual-contributor role. You'll define architecture, write specs, lead design reviews, and get your hands dirty in integration testing and flight trials. If you're the kind of engineer who wants to see their decisions fly, read on.
Duties
• Onboard compute & system architecture — Select and justify UAV hardware, define thermal management, memory, and power budgets within tactical SWaP constraints. Produce and maintain ICDs, system block diagrams, requirements decomposition trees. • Cross-functional technical leadership — Drive architecture decisions across firmware, ML, flight controls, payload, RF, and test engineering through design reviews, trade studies, and risk assessments. • AI inference pipeline — architect the sensor-fusion and inference stack: raw multi-modal input (EO/IR, thermal, RF). Own the model on board lifecycle. • GNSS-denied navigation — implement positioning architectures that hold up under EW-contested and GNSS-denied conditions. • Multi-vehicle coordination — architect swarm topologies with real-time task allocation, formation management, autonomous re-planning when needed. • Communications & networking — collaborate on defining the communications architecture across the platform stack. • Safety-critical decision logic — design fail-safe behaviors (abort, return-to-base, self-destruct triggers), HITL and HOTL authorization gates. • Security architecture — Define security integration, cryptographic chain-of-custody for operator decisions, and compliance mapping to relevant standards. • Verification & validation — Define acceptance criteria, HIL/SIL test architectures, scenario scripting, fault injection, and performance benchmarking. • Systems engineering documentation — Own ConOps, SRS, and ICD documents.
This is a systems engineering role as much as it is a software role.
Competences & Skills
Required:
• Master's in Electronic Engineering, Computer Science, Aerospace, Robotics, or related field (Bachelor's accepted with strong experience; PhD is a plus) • 5+ years in systems architecture, embedded systems, or autonomy engineering in aerospace, defence, or robotics • 2+ years experience with developing UAS, autonomous vehicles, or comparable real-time robotic platforms • Proven AI/ML inference deployment on embedded hardware under real-time SWaP constraints, including quantization, optimization, and lifecycle management • Knowledge of RTOS, embedded Linux, and deterministic scheduling for safety-critical applications • Hands-on GNSS-denied navigation: VIO, SLAM, inertial navigation, and multi-source position fusion • Demonstrated multi-agent autonomy design: swarm coordination, distributed task allocation, and mesh networking • Safety-critical systems background: fail-safe logic, fault-tree analysis, hazard assessment, HITL/HOTL architectures • Solid systems engineering fundamentals: requirements decomposition, traceability, V-model V&V, and configuration management • Embedded security architecture: secure boot, HSM integration, key management, and tamper-evident logging • Systems modelling fluency: SysML/UML, ICDs, ConOps, trade-study frameworks • Comfortable reading and writing C, C++, and Python across firmware, middleware, and application layers • Experience with ROS 2, PX4/ArduPilot, MAVLink, or UAVCAN • Ability to lead cross-functional teams without direct authority — aligning firmware, ML, hardware, RF, and test engineers around shared architectural decisions • Strong written communication: clear specs, ICDs, trade studies, and technical risk assessments that actually drive decisions • Comfortable in field-test and HIL environments; willing to support flight trials and rapid iteration cycles • English — Advanced or above
Preferred:
• 2+ years deploying edge AI on UAS, autonomous vehicles, or comparable real-time robotic platforms • ML deployment toolchains: TensorRT, ONNX Runtime, OpenVINO, or Hailo Dataflow Compiler • Defence standards familiarity: DO-178C, MIL-STD-882E, STANAG 4586, MISRA C, FIPS 140-2 • Prior flight-test experience with autonomous aerial platforms, including test-plan authoring and post-flight analysis • Onboard mission planning, path optimization, VRP solvers, or Kalman-filter-based tracking • Embedded Linux build systems (Yocto, Buildroot) and custom board bring-up • Publications at ICRA, IROS, CVPR-UAV workshops, or IEEE Aerospace • Background in ISR, SIGINT, EW, or strike mission domains