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UiPath is seeking a Principal Product Designer to own the end-to-end experience for one of its Vertical Solutions—high-stakes domains including healthcare, financial services, supply chain, and manufacturing where agentic AI makes critical decisions alongside human oversight.
You will design for a specific vertical while establishing generalized patterns that scale across all verticals. Your responsibilities span three interconnected areas: (1) the reviewer experience—the screens and workflows where humans make accountable decisions on AI-assisted outcomes; (2) how agents learn from domain experts and how that learning remains transparent and auditable; and (3) the administration and configuration experiences that bring customers live.
This is a hands-on role where design and engineering are deeply integrated. You will work in code (primarily Claude Code and modern frontend stacks), move from concept to working prototype in days, and ship directly into the product repository. You report to the Senior Director of Design for Vertical Solutions and collaborate closely with product managers, engineers, and cross-vertical design partners.
You own business outcomes—design is measured against product metrics, and you establish baselines and quantify design influence. You work horizontally across teams, ensuring your vertical's solutions generalize without losing coherence. You engage directly with customers to understand their needs, spot gaps early, and maintain a consumer-grade experience bar in a regulated, high-stakes environment.
Required: 10+ years owning meaningful product areas with demonstrated ability to think deeply about user needs, not just surface requests. You must be comfortable with modern frontend development, GitHub, Figma, and Claude.ai. You should be able to hold your position in rooms with designers, PMs, and engineers, articulating both the design rationale and the business case.
Preferred: Experience designing AI or agentic products (especially human oversight, trust, memory, governance), familiarity with regulated or operationally complex industries, knowledge systems, or internal tools where accumulated knowledge must remain trustworthy.
