Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Candidates for this role will lead simulation-driven testing, automation, and software quality efforts for Hivemind, building and executing test frameworks that ensure our autonomy software performs reliably across simulated and real-world mission environments. Shield AI is growing quickly, and we're looking for someone who thrives in fast-paced environments, embraces learning, and brings a high-ownership, mission-driven mindset. This is a chance to have a real impact—advancing autonomy that protects lives—while working with a collaborative, high-performing team.
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Our international teammates receive a comprehensive total rewards package aligned to your country office location. For full details on compensation and benefits, please consult your talent acquisition partner.
What you'll do:
Develop automated regression, integration, and system-level tests to ensure Hivemind software quality and stability across releases
Identify, reproduce, and diagnose software issues—collaborating closely with development teams to drive fixes and improvements
Create and execute test plans and documentation for autonomy software in simulated environments, ensuring mission and safety requirements are met
Design, implement, and maintain simulation-based test frameworks to validate Hivemind autonomy behavior and performance
Build tools and utilities in Python to automate testing, data processing, and analysis workflows
Develop test harnesses and data validation tools for Software-in-the-Loop (SIL) / Hardware-in-the-Loop (HIL) / Vehicle-in-the-Loop (VIL) and simulation environments
Contribute to the definition of testing methodologies, metrics, and performance benchmarks for autonomy software validation
Support the scaling and reliability of simulation infrastructure used for large-scale software validation
Maintain detailed and accurate test documentation, ensuring traceability and knowledge sharing across teams
Work with developers to integrate test coverage directly into the development pipeline (CI/CD)
Required qualifications:
Typically requires a minimum of 7 years of related experience with a Bachelor’s degree; or 5 years and a Master’s degree; or 4 years with a PhD; or equivalent work experience.
Proficiency in Python.
Experience in robotics, small UAS, or related hands-on engineering projects
Strong analytical, problem-solving, and debugging skills * Passionate about intelligent aircraft systems.
Excellent communication and collaboration skills, with the ability to work effectively with cross-functional software, hardware and mechanical engineering teams.
Adaptability and a willingness to learn new technologies and methodologies quickly in a fast-paced environment.
Preferred qualifications:
Experience testing autonomous systems, robotics software, or flight autonomy algorithms.
Familiarity with C++ and software/hardware integration concepts.
Experience with HIL or VIL test environments.
Exposure to machine learning or AI-driven autonomy systems.
Background in simulation infrastructure design, distributed testing, or test data management.
Quality Assurance (QA) experience, including process definition, metrics, and validation tracking.
Experience with aerospace, defense, or mission-critical software.
