Job Description:

About the Role

The era of the pixel-pushing specialist is ending. We're hiring a Product Designer II who operates as an early-stage Product Builder and someone who pairs solid design craft with AI-augmented research, vibe design workflows, and an evaluation mindset. You won't just hand off mockups; you'll guide AI agents to generate production-ready UI, run research at a scale one person couldn't reach before, and pour your hands-on craft into the 10% of the experience that makes a product feel magical.

You'll own a defined product area within HPE to assistant, self-driving workflows and automated actions, or assurance dashboards  partnering closely with your PM and engineers to frame problems clearly, explore solutions broadly, and ship work that connects to real business outcomes for IT operators.

As a UX designer on the team, your users are network admins, engineers, and IT leaders drowning in complexity. Your job is to turn billions of telemetry data points, AI-driven insights, and agentic workflows into experiences that feel clear, trustworthy, and even delightful to help IT teams find and fix problems before end users ever notice them. Few design teams anywhere get to work this deep at the intersection of conversational AI, agentic automation, and data-dense enterprise UX.

Location:

This is a hybrid role based in Bengaluru, India. You'll be expected in the office 2 days per week to collaborate in person with your product, engineering, and design partners.

What You'll Do

Product Sense

• Know your product area deeply: understand the jobs to be done, how competitors solve them, and where the gaps are.
• Frame your work so it clearly ladders up to the long-term product vision; assist PMs and senior designers in bringing strategic vision work to life through mocks, decks, and written narratives.

Research & Insight (Pillar 1 — Scaled Empathy)

• Define the questions to ask and the problems to explore; state clear problem statements grounded in research and data, and align your team on them before designing.
• Run AI-scaled qualitative research: use tools in the class of User Intuition, Listen Labs, and Perspective AI to automate recruiting, moderate asynchronous interviews, and adaptively probe "why" across hundreds of users.
• Synthesize unstructured data — support calls, transcripts, feedback, tickets — into converged insight using AI thematic clustering (e.g., Dovetail, CoLoop, Enterpret).
• Interpret product metrics and make data-informed decisions; use AI-native analytics (e.g., Fullstory frustration signals, Mixpanel/Amplitude AI assistants) to diagnose behavior and connect findings directly to design choices.

Craft & Vibe Design (Pillar 2 — From Pushing Pixels to Vibe Design)

• Explore a wide breadth of visual directions and articulate the trade-offs of each; know when an industry pattern works and when it should be pushed further.
• Build prototypes that go beyond click-throughs — motion, transitions, and states that feel like the real thing. Increasingly, prototype in working front-end code by guiding AI agents (VS Code, Claude Design, Lovable, v0, Cursor, Replit, Bolt) that are grounded in our design system, accessibility standards, and user context.
• Practice the Product Builder working mindsets:
  • Embrace the Error — feed error output back to the agent and keep momentum instead of hand-debugging.
  • Stand on Giants — inject codebase and design-system context, reach for existing libraries before building from scratch.
  • Parallel Commander — run multiple agent workstreams concurrently and context-switch between them deliberately.
• Consider edge cases when designing within complex systems; document your part of the system so others can build on it.

Innovation Moat (Pillar 3 — The 90/10 Rule)

• Let AI generate the 90% of commodity UI (forms, lists, settings) quickly — then invest your full manual craft in the 10% magical experience that AI can't replicate: the product's soul.
• Contribute components and patterns to the design system as a "UI toolbox" that AI agents can reliably assemble from — the foundation of Generative UI.

Evaluation (Pillar 4 — Agent Eval)

• Treat AI features as non-deterministic systems: help define what "good" and "bad" experiences look like before shipping.
• Contribute subjective rubrics — clarity, helpfulness, tone, and brand alignment — that make experience quality measurable.
• Partner with research and PM on golden datasets and operating limits, and support the path toward scaled evaluation (LLM-as-a-Judge) rather than one-off spot checks.

Collaboration & Impact

• Communicate clearly and concisely in writing; present work with a clear narrative and good context-setting, and grow your confidence leading meetings.
• Maintain a predictable, transparent process — partners always know your priorities and cadence. Manage your bandwidth and speak up when your plate is full; triage feedback diligently so nothing falls through the cracks.
• Understand how your work contributes to the business and prioritize accordingly; follow through post-launch, host bug bashes, and propose improvements to lift your work's impact.
• Help other designers grow through feedback and skill shares; suggest and implement team culture improvements.

What You Need To Bring:

• Minimum of 3-5 years of product design experience.
• Strong foundations in visual design, interaction design, and design systems, with a 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) and 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.

Nice to Have

• 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.

Accessibility

HPE is committed to creating an inclusive and accessible workplace and encourages applications from all qualified individuals, including those with disabilities. If you believe you require accommodation during any stage of the application or interview process, please submit your request by completing our secure form linked here.

Note: This option is reserved for applicants needing assistance/reasonable accommodation related to a disability.

Health & Wellbeing

We strive to provide our team members and their loved ones with a comprehensive suite of benefits that supports their physical, financial and emotional wellbeing.

Personal & Professional Development

We also invest in your career because the better you are, the better we all are. We have specific programs catered to helping you reach any career goals you have — whether you want to become a knowledge expert in your field or apply your skills to another division.

Unconditional Inclusion

We are unconditionally inclusive in the way we work and celebrate individual uniqueness. We know varied backgrounds are valued and succeed here. We have the flexibility to manage our work and personal needs. We make bold moves, together, and are a force for good.

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Hewlett Packard Enterprise is EEO Protected Veteran/ Individual with Disabilities.

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