Embedded Linux / Edge Autonomy Engineer

NODA AI•Austin, TX

2d•Hybrid

About The Position

NODA is a veteran-owned, venture-backed technology company transforming how unmanned systems collaborate in complex, mission-critical environments. Our distributed orchestration platform enables autonomous coordination of heterogeneous unmanned systems across air, sea, land, and space with vital applications in the defense, intelligence, and commercial sectors. We build autonomy that runs both at the edge—under real-world constraints—and at the platform level, where mission intent, orchestration, and AI-driven decision-making come together. Reliability, explainability, and performance on real hardware are foundational to our work. We are seeking a Systems Engineer – Edge & Autonomous Systems to bring up and harden edge-resident autonomy capabilities on real hardware and integrate them into a broader autonomous orchestration platform. This role focuses on making autonomy work outside the lab: on Linux-based edge compute, under degraded communications, constrained resources, and heterogeneous vendor environments. You will work at the intersection of embedded systems, operating systems, networking, and autonomy software, ensuring deterministic, observable, and field-ready behavior. In this role, you will get hands-on exposure to both: Edge AI and supervisory autonomy running adjacent to vehicles, and Platform-level autonomous orchestration and AI systems coordinating behavior across fleets and domains. This is a hands-on, execution-oriented role for engineers who are comfortable debugging real systems, measuring performance directly, and making things work under pressure.

Requirements

5+ years of experience in systems engineering, embedded software, or edge computing roles.
Strong experience developing and debugging software on Linux-based embedded or edge systems.
Proficiency in C++ and/or Python for systems-level development and tooling.
Hands-on experience profiling CPU, memory, latency, and I/O performance on real hardware.
Solid understanding of networking fundamentals (TCP/UDP, latency, packet loss, bandwidth constraints).
Experience with network diagnostic tools (tcpdump, Wireshark) for debugging latency, packet loss, and protocol issues.
Comfort using hardware debugging tools such as multimeters and oscilloscopes.
Experience integrating software with real hardware, sensors, or controllers.
Familiarity with hardware communication buses (SPI, I2C, UART) and their use in sensor and controller integration.
Ability to operate effectively in fast-moving environments with evolving requirements and tight timelines.
U.S. Citizenship with the ability to obtain a security clearance.

Nice To Haves

Experience working adjacent to flight controllers or autonomy stacks (without modifying them).
Background in aerospace, defense, robotics, or other mission-critical embedded systems.
Familiarity with ROS 2 or robotic middleware (helpful but not required).
Experience with event-driven or state-machine-based system design.
Prior involvement in field testing, demos, or operational deployments.
Experience designing systems that are vendor-agnostic and portable across hardware platforms.
Exposure to Rust for systems-level development; interest in applying it to edge and safety-critical workloads is a plus.

Responsibilities

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.