Senior Staff Engineer, Autonomy Integration Lead

About the role

Shield AI is a venture-backed defense-tech company whose Hivemind Pilot group builds AI/autonomy software that lets teams of edge systems perceive, reason and act in complex mission environments. As Autonomy Integration Lead, you bring together autonomy components into integrated reference implementations and take them through software-in-loop and hardware-in-loop verification.

Key responsibilities

• Build and maintain stable Pilot integrated implementations, reference configurations, reusable test fixtures and end-to-end examples.
• Partner with component teams to add capabilities to the shared integration environment, maintain the integration baseline and resolve gaps in workflows, test harnesses or extensibility.
• Develop and maintain automated software-in-the-loop and hardware-in-the-loop tests covering autonomy components.
• Maintain the glue layer between mission autonomy software and platform software for easy integration and deployment.
• Investigate failures across system boundaries, reproduce and instrument problems, isolate the responsible layer, fix integration defects and provide evidence to the owning team.
• Support deployment of the integrated autonomy stack to representative hardware, including software configuration, telemetry, interface troubleshooting and lab or field debugging.
• Work with the Flight Operations team on test objectives, readiness assessment, troubleshooting during tests and post-test analysis.
• Write setup guides, reference configurations, troubleshooting runbooks and executable examples, and contribute technical material to Pilot training.

Required profile

• Bachelor's degree in Computer Science, Robotics, Artificial Intelligence or equivalent practical experience.
• Demonstrated experience building, testing and debugging nontrivial C++ software for perception, planning, robotics or autonomous systems.
• Experience with modern C++ and debugging issues such as data races, deadlocks and lifetime errors.
• Experience with Linux, build and dependency management tools such as Conan or Nix, and strong software engineering fundamentals.

Preferred qualifications

• Master's degree in AI, Computer Science, Robotics or similar.
• Breadth of experience across the autonomy stack (perception, localization and planning).
• Multi-agent autonomy, VLMs or VLAs, and software for fielded, real-time, safety-critical systems.
• Software-in-the-loop or hardware-in-the-loop simulation, performance profiling or distributed systems.