Noda

Solutions Engineer

• Serve as a day-to-day technical bridge between Solutions Engineering and Field Operations to ensure systems are built and configured in alignment with NODA architecture and mission requirements
• Support hands-on integration, bring-up, and troubleshooting of radios, onboard compute, payloads, networking components, and unmanned platforms
• Configure and debug onboard autonomy stacks (PX4, ArduPilot), including parameters, modes, and failsafe behavior
• Understand and troubleshoot autopilot state machines, flight modes, and mission execution behavior
• Manage and debug MAVLink communication, including routing, multiplexing, and telemetry flow between components
• Integrate autopilot systems with radios, onboard compute, and mission control systems (e.g., URZA/Maestro)
• Debug integration issues across hardware, software, networking, and configuration layers using structured, step-by-step approaches
• Read and interpret logs, configs, interface definitions, and system outputs to diagnose issues and validate system behavior
• Write or modify scripts and configuration files to improve setup, automation, and repeatability of integration workflows
• Support development and execution of validation workflows including SITL, HITL, and field testing
• Contribute to containerized test and qualification frameworks for unmanned systems prior to URZA integration
• Ensure field-built systems do not diverge from NODA’s architecture, software assumptions, and communications design
• Support field exercises and mission events by validating system readiness and assisting with rapid issue resolution
• Capture recurring failure modes, integration issues, and field learnings to improve reliability and execution quality over time
• Collaborate with engineering teams to surface systemic issues and improve integration patterns, tooling, and workflows

Field Systems Integration Engineer

Artificial Intelligence

• Design and implement autonomy modules including path planning, task allocation, behavior trees, and reactive execution models.
• Develop and maintain the autonomy framework that integrates with orchestration (AI-driven mission planning) and world modeling.
• Ensure AI-generated plans are executable, explainable, and safe across multi-domain robotic platforms.
• Implement and validate navigation, control, and autonomy behaviors for UAVs, USVs, and UUVs using ROS2 and simulation environments.
• Profile and optimize autonomy performance for edge compute hardware (Jetson, Raspberry Pi-class devices).
• Conduct simulation-in-loop and hardware-in-loop testing to validate autonomy behaviors before live field deployment.
• Contribute to safety, reliability, and compliance practices for autonomy in defense-relevant missions.
• Collaborate across AI, networking, and systems engineering teams to ensure seamless orchestration of multi-vehicle operations.

Autonomy Engineer, AI

Full-stack Engineer

• Design and implement offline-first supervisory behavior (connected / disconnected / rejoin), including store-and-forward telemetry and deterministic safe-state escalation.
• Bring up and validate autonomy software on real edge compute hardware running Linux.
• Integrate autonomy components with live telemetry and command interfaces using standard protocols.
• Measure and profile CPU utilization, memory usage, I/O behavior, and end-to-end latency under nominal and degraded conditions.
• Implement and validate event-driven, deterministic logic that supervises autonomous behavior based on communications and system health.
• Diagnose and debug issues related to networking degradation, packet loss, timing jitter, and heartbeat gaps.
• Instrument systems for observability and explainability, ensuring behavior is traceable via logs and telemetry.
• Use hardware debugging tools (multimeter, oscilloscope, logic analyzer as needed) to troubleshoot power, signal, and I/O issues.
• Support simulation-in-the-loop testing where useful, while prioritizing validation on real hardware.
• Collaborate with autonomy engineers, platform engineers, mission leads, and field operations to ensure systems behave predictably during demos and deployments.
• Rapidly troubleshoot and stabilize systems during field tests and customer-facing events.
• Own health modeling and watchdog patterns (heartbeat, staleness, escalation, safe state) for vehicle supervisors.

Field Systems Integration Engineer

Autonomy Engineer, AI

Embedded Linux, Edge Autonomy Engineer