This role centers on the design of AI agents that do not merely respond to prompts, but can interact with engineering artifacts, reason over goals and constraints, and improve their behavior through feedback, simulation, and optimization. This includes defining suitable state and action representations for technical workflows, integrating symbolic and structured knowledge, designing reward mechanisms aligned with engineering objectives, and building simulation or surrogate environments in which agents can learn safely and efficiently. + ability to design agents that learn from interaction, simulation, or structured feedback in complex environments + strong interest in applying AI to systems engineering tasks such as design-space exploration, requirement analysis, architecture optimization, verification support, or engineering workflow automation
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