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Shield AI

Builds autonomous aircraft for defense

Senior Engineer - C++ Software

Desktop Application DevelopmentUpdated on Nov 14
Full-timeMelbourne VIC, AustraliaNo salary listedIn-person

About the Job

Requirements

  • A degree in Computer Science, Software Engineering, Electrical Engineering, Robotics, or a related discipline, or equivalent industry experience.
  • Extensive industry experience developing modern C++ software for Linux.
  • Demonstrated experience developing user-space applications that interface with cameras, sensors, networking, GPUs, storage, or other hardware through operating system APIs, middleware, or vendor SDKs.
  • Deep practical experience developing, profiling, and debugging software on Linux.
  • Experience deploying complex C++ software to Linux-based edge compute platforms such as NVIDIA Jetson or comparable ARM64 systems.
  • Strong software engineering fundamentals, including concurrency, interface design, memory management, data structures, algorithms, testing, and version control.
  • Proven ability to diagnose complex issues across software, Linux, networking, timing, hardware integration, and deployment boundaries.
  • Experience owning complex technical work from incomplete requirements through design, implementation, integration, verification, deployment, and support.
  • A sustained record of defining architecture for large, complex, or mission-critical software systems.
  • Demonstrated technical influence across multiple teams, products, or engineering disciplines.
  • Leadership of complex initiatives where success depended on alignment across organisational boundaries.
  • Proven technical leadership through influence, sound judgement, and credibility rather than organisational authority.
  • Experience mentoring senior engineers and developing other technical leaders.
  • Ownership of long-term technical strategy alongside hands-on engineering and product delivery.
  • Evidence of establishing platforms, standards, interfaces, or engineering practices adopted beyond the immediate team.
  • Strong judgement when balancing performance, reliability, maintainability, scalability, delivery, and operational risk.
  • The ability to communicate technical strategy, decisions, and risks to senior engineering, product, and business stakeholders.

Responsibilities

  • Own and evolve the technical direction of significant edge software capabilities spanning edge compute, imaging, sensor integration, and mission systems.
  • Define architecture and technical strategy across multiple projects, products, and engineering teams.
  • Lead the resolution of complex, ambiguous, or cross-cutting technical problems where ownership spans organisational boundaries.
  • Establish reusable platform capabilities, interfaces, standards, and engineering practices adopted by multiple teams.
  • Provide technical leadership for major design decisions, including their trade-offs, risks, migration strategies, and long-term consequences.
  • Identify systemic technical risks and drive coordinated action before they materially affect delivery or product reliability.
  • Mentor senior engineers and develop other technical leaders, increasing the capability and autonomy of the wider organisation.
  • Partner with engineering, systems, autonomy, AI, product, and program leadership to translate business and product direction into sustainable technical roadmaps.
  • Balance long-term platform investment, technical debt, operational risk, and near-term product delivery.
  • Communicate complex technical decisions, strategy, and risks clearly to engineering and non-engineering stakeholders.
  • Design, develop, test, and maintain production C++ software for edge systems, imaging systems, mission applications, developer tooling, diagnostics, and automated testing.
  • Build user-space Linux applications for NVIDIA Jetson, ARM64, and other edge compute platforms connected to cameras, sensors, and mission systems.
  • Integrate RGB, NIR, and thermal cameras alongside GPS, IMU, and other sensors using operating system APIs, middleware, vendor SDKs, and hardware-facing interfaces.
  • Develop calibration, synchronisation, data capture, observability, diagnostics, inspection, and configuration tools for complex sensor systems.
  • Optimise software for latency, throughput, reliability, power utilisation, and thermal performance on constrained edge compute platforms.
  • Debug challenging issues spanning application software, Linux, networking, hardware interfaces, timing, deployment, and system integration.
  • Own technical outcomes for complex, cross-team initiatives from ambiguous problem framing through architecture, implementation, integration, verification, deployment, and sustained operation.
  • Collaborate across systems, hardware, AI, autonomy, product, and test teams to deliver integrated capability.

Desired Qualifications

  • Experience with runtime-critical, multi-threaded, or performance-sensitive C++ software.
  • Experience with high-throughput imaging or sensor-processing pipelines, including camera integration, ISP tuning, GStreamer, FFmpeg, OpenCV, or similar technologies.
  • Experience with hardware-accelerated processing on edge compute platforms, including NVIDIA Jetson, CUDA, GPU compute, embedded AI accelerators, or accelerated video processing.
  • Experience integrating RGB, NIR, and thermal cameras, GPS, IMU, GPUs, or comparable peripheral hardware.
  • Experience in robotics, aerospace, defence, autonomy, unmanned systems, automotive, or other mission-critical domains.
  • Experience with systems architecture, interface design, software decomposition, reliability, maintainability, and testability.
  • Experience with low-level Linux, vendor SDKs, driver-adjacent debugging, NixOS, edge AI inference, containerisation, or application deployment tooling.
  • Experience with automated testing, simulation, software-in-the-loop, or hardware-in-the-loop environments.

About the Company

Shield AI

Builds autonomous aircraft for defense

Shield AI builds autonomous aircraft and flight software for military and allied defense customers, with a focus on operations where conventional remote control breaks down. Its Hivemind AI pilot handles decisions during a mission, while the V-BAT aircraft gathers intelligence and locates targets. Aircraft makers use its software tools to develop and test their own autonomy, and its Aechelon business supplies visual and sensor simulation for pilot training. The company earns money from aircraft sales, autonomy software and contracted engineering and operational services. Shield AI was founded in 2015 and is headquartered in San Diego, California.

Company size
1,001-5,000
Company stage
Debt Financing
Total funding
$4.8B
Headquarters
San Diego, CA
Founded
2015

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