Modelling and Simulation Lead
Shield AI is a U.S. defense-technology company developing mission-autonomy software and autonomous aircraft for military and allied operations.
Funding history
Investors
About Shield AI
Founded in 2015, Shield AI builds Hivemind autonomy software and V-BAT and X-BAT aircraft for operations in contested, GPS- and communications-denied environments. Its current site also presents Aechelon synthetic-reality simulation and Vision Systems detection and tracking products.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will lead the design, development, and integration of simulation and test environments for uncrewed-aircraft autonomy. You will guide multidisciplinary engineers, build high-performance real-time simulation software, integrate defence simulation frameworks and hardware-in-the-loop systems, deploy containerized environments, and improve delivery practices.
Requirements
- A tertiary qualification in Computer Science, Software Engineering, Mechatronics, or a related field
- Extensive software engineering and systems-integration experience
- Strong experience in modern C++ and familiarity with legacy standards
- Professional Python experience
- Experience delivering reliable software systems in fast-paced environments
- Experience leading teams to deliver complex engineering projects
- Experience with real-time distributed simulation systems or HWIL or SWIL environments
- Experience with containerization technologies
- Experience working in Linux development environments
- Ability to obtain an Australian NV1 security clearance
Responsibilities
- Lead the design and evolution of distributed real-time simulation systems
- Architect and implement C++ software for modelling, simulation, and integration workflows
- Develop, optimize, and deploy software for real-time mission-execution environments and multi-agent simulations
- Apply defence simulation frameworks including AFSIM or NGTS
- Use containerization technologies for scalable simulation deployments
- Lead engineering teams of five or more contributors
- Integrate simulation with autonomy algorithms, hardware interfaces, and test pipelines
- Champion CI/CD, test-driven development, design patterns, and system architecture practices
