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.
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.
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.
