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Noda Ai

Senior Systems Software Engineer

AustinHybrid · United States
Senior · FullTime · Engineering
POSTED 22 JULVERIFIED 8H AGO
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110 days opentrue age
Posted 22 Jul
Pay
$158k–$214kno pay posted
Market p25–p75
$158k–$214k
Austin · n=41 · 365d to 6 Nov
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PythonGoC++Distributed systems

Senior Systems Software Engineer

Location: Austin, TX (Hybrid on-site, with travel)

Travel: ~20% typical; up to ~50% during field exercises and partner/military deployments

Clearance: U.S. Citizen with the ability to obtain a security clearance

About NODA

NODA is a veteran-owned, venture-backed technology company transforming how unmanned systems collaborate in complex, mission-critical environments. As NODA scales across products, partners, and deployment environments, keeping the system coherent in practice — not just on paper — is what separates a platform that works in the field from one that only works in a demo.

Our Systems Software Engineers are the people who can stand at the seam between subsystems — software, networking, RF, and hardware — and make sense of what's actually happening when something breaks in degraded, contested, or denied conditions. You won't be the deepest RF, networking, or hardware specialist in the room, but you'll be able to hold your own in that conversation, pinpoint where in the stack a problem actually lives, and write the software — or pick up a multimeter — needed to prove it.

The Role

As a Systems Software Engineer, you will work across NODA's cross-system infrastructure — the messaging fabric, gateway, and runtime built on real-time messaging frameworks (DDS, ROS/ROS2, and similar) that coordinate fleets of heterogeneous unmanned systems in real time — debugging and resolving issues that don't respect team boundaries. You'll pinpoint performance and integration issues end to end, write software stacks under a systems architect's supervision where the work falls outside Core Engineering's product ownership, and work directly with networking, RF, and hardware subject matter experts when an issue requires investigation below the software layer. You'll also support the System Health function — characterizing performance baselines, analyzing crashes to root cause, and producing the verification evidence the organization relies on for release decisions.

Key Responsibilities

Debug and resolve cross-system issues spanning software, real-time messaging, networking, RF, and hardware — owning the investigation even when the root cause sits outside your primary depth

Pinpoint performance and latency issues in cross-system infrastructure (messaging fabric, gateway, runtime) supporting multi-agent coordination, and drive them to resolution

Write and maintain software stacks under a systems architect's supervision, for work outside Core Engineering sub-teams' product ownership

Investigate and characterize system behavior under degraded, intermittent, or contested link conditions

Perform hands-on hardware diagnostics using basic bench tools (multimeter, oscilloscope) to isolate issues at the hardware/software boundary

Hold credible technical conversations with networking, RF, and hardware SMEs — translate their findings into system-level constraints and software fixes

Contribute to System Health: performance baselining, system-level verification, crash analysis to root cause, and KPI/dashboard evidence used for release go/no-go decisions, with a focus on driving measurable improvements in latency, reliability, and uptime

Identify and mitigate cross-system risks impacting mission effectiveness, including in live exercises or deployments

Support integration tooling, CI/CD for cross-system components, and automated regression in SIL/HIL environments

Maintain Interface Control Documents and integration contracts between major platform components, and translate field/operational requirements into system constraints Core Engineering and architects can build against

Build observability into cross-system components (logging, tracing, metrics) to make the next debugging pass faster

Required Qualifications

5+ years of professional software engineering experience, including significant time debugging distributed, real-time, or multi-service systems in production

Strong proficiency in C++ and/or Python, with the ability to write production-quality software with architect-level supervision on system design

Source · Noda AiFirst seen 2 NovOriginal ↗