Staff Engineer, Systems (R4624)

Bachelor’s degree with approximately 7+ years of relevant experience, or Master’s degree with approximately 5+ years of relevant experience, in Systems Engineering, Aerospace Engineering, Robotics, Software Engineering, or a closely related technical field with demonstrated experience working on complex software or autonomous systems.

Strong experience with MBSE practices, including practical application of SysML v1.6 and familiarity with SysML v2 concepts.

Hands-on experience with Cameo Systems Modeler or equivalent MBSE tools. Ability to translate complex technical systems into clear, structured models and narratives. The ability to create effective diagrams using best practices for visual design (groupings, alignment, color, etc.) using non-MBSE-specific tools (such as Lucid, Visio, or similar diagramming software).

Proven ability to understand, model, and reason about large-scale autonomy software systems and developer-focused SDKs.

Strong understanding of modern software engineering practices, including CI/CD, automated testing, configuration management, and software lifecycle processes.

Experience working cross-functionally with software engineers, autonomy / AI engineers, test engineers, product managers, and UX / GUI teams.

System modeling and MBSE:

Develop and maintain high-quality system models that describe architecture, behavior, interfaces, and data flows across the Hivemind SDK. Apply MBSE principles using SysML v1 and v2, while remaining tool-agnostic and able to model effectively using Cameo, Lucid, and other general-purpose diagramming or flow-chart tools when appropriate.

Cross-stack system understanding:

Work closely with engineers across the entire product stack—including foundational software, autonomy and AI algorithms, simulation and test infrastructure, and GUI layers—to capture an accurate and fully detailed model of the Hivemind SDK product.

Process and lifecycle modeling: Model internal engineering processes such as software development lifecycle workflows, CI/CD pipelines, testing and release processes, and configuration management to improve shared understanding and enable continuous improvement.

Architecture definition and analysis

Founded in 2015, Shield AI is a venture-backed deep-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include the V-BAT and X-BAT aircraft, Hivemind Enterprise, and the Hivemind Vision product lines. With offices and facilities across the U.S., Europe, the Middle East, and the Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit

www.shield.ai

. Follow Shield AI on

LinkedIn

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