UX Product Designer (Networking)
HybridAll, Catalunya, Kingdom of Spain
Job Summary
Conduct AI-augmented UX design for HPE's networking products, guiding agents to generate production-ready UI and automate research across hundreds of users. Synthesize unstructured data and metrics into converged insights to frame problems and ship experiences that help IT operators manage complex telemetry. Build prototypes in working front-end code using design systems and contribute components to a reusable UI toolbox for generative workflows. Define evaluation rubrics and golden datasets for AI features, partnering with research and engineering to scale quality assurance. Collaborate with product managers to align work with long-term vision, present clear narratives, and triage feedback to maintain predictable cadence.
Required Qualifications
- Minimum of 2 years of product design experience
- Strong foundations in visual design, interaction design, and design systems
- Portfolio showing breadth of exploration and articulated trade-offs
- Hands-on fluency (or demonstrated fast learning) with at least one AI design-to-code / vibe design tool (e.g., VS Code, Claude Design, Lovable, v0, Cursor, Replit, Bolt, Stitch)
- Hands-on fluency (or demonstrated fast learning) with one AI research or analytics tool (e.g., Dovetail, Perspective AI, Fullstory, Mixpanel)
- Comfort working with data: you can read a funnel, question a metric, and let evidence guide your design decisions
- A builder's temperament: bias toward working prototypes over static specs, curiosity over fear when tools break, and pride in the details that make an experience feel crafted rather than generated
- Onsite role with expectation to primarily work from an HPE office
- Hybrid role based in Cupertino, CA
- Expected in the office 2 days per week to collaborate in person with product, engineering, and design partners
Desired Qualifications
- Experience designing for AI/agentic products (chatbots, copilots, generative UI)
- Exposure to evaluation practices for AI systems (rubrics, golden datasets, LLM-as-a-Judge)
- Familiarity with front-end fundamentals (React, Tailwind, component architecture) — enough to guide and review agent-generated code
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