The Hivemind Platform Team at Shield AI is seeking a highly skilled and detail-oriented Systems Modeler to join our team.
\nThe Hivemind Enterprise product is a software development kit (SDK) that enables scalable design, deployment, evaluation, and iteration of autonomy architectures for a wide range of robotic platforms.
\nAs a Systems Modeler for Hivemind at Shield AI, you will be a key member of a multidisciplinary Systems Engineering team, working collaboratively with Product, technical individual contributors, and Test / Quality Assurance team members to define, model, and communicate the structure and behavior of complex autonomy software systems.
\nThis role focuses on building and maintaining system models that span the full product stack,from foundational software and autonomy algorithms to developer infrastructure to user-facing interfaces.
\nIn addition to modeling the Hivemind SDK product, you will also use your skills to help us improve our internal engineering processes, modeling the design of the systems that support product development such as CI/CD pipelines, test and configuration systems, and software and product life cycle processes.
\nWhile your primary focus will be systems modeling, as part of a full Systems Engineering team, you will also support your team members as needed by helping with functions such as requirements development.
\nThis role is hands-on and highly collaborative, requiring deep expertise in systems modeling and Model-Based Systems Engineering (MBSE), strong software system intuition, and working knowledge of autonomous software pipelines.
\nAs a Systems Modeler on the Hivemind team, you will help create a shared, rigorous understanding of one of Shield AI’s most complex and critical software products.
\nYour models will shape architecture decisions, enable cross-team alignment, and ensure that Hivemind continues to scale as a robust autonomy platform.
\nWHAT YOU'LL DO:
\nSystem modeling and MBSE: Develop and maintain high-quality system models that describe architecture, behavior, interfaces, and data flows across the Hivemind SDK.
\nCross-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.
\nProcess 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.
\nArchitecture definition and analysis: Support system architecture trade studies, identify dependencies and constraints, and analyze impacts of design decisions across software components, development workflows, and operational use cases.
\nRequirements support: Ensure alignment and traceability between requirements and system models.
\nCommunication and documentation: Use system models as a primary communication artifact to align stakeholders, surface risks and gaps, and enable informed technical decision-making across teams.
\nREQUIRED QUALIFICATIONS:
\nPREFERRED QUALIFICATIONS:
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