Product Designer: AI & Complex Flows

WhyHireWrong?Capon Bridge, WV
10d

About The Position

Most AI products are built by people who understand the technology. What they often miss is the human on the other side of the screen, confused, rushed, sometimes anxious, trying to make a decision that matters. This role is about bridging that gap. You will design interfaces where AI genuinely helps people: not by doing more, but by doing the right thing at the right moment. You will use AI tools in your own process — to prototype faster, test smarter, and iterate with intent. We are looking for someone who is thoughtful, curious, and experienced, and who sees inclusive design not as a constraint but as a foundation.

Requirements

  • Hands-on experience with AI in your design process. You use AI tools actively to prototype, generate layout variants, write microcopy drafts, or speed up research synthesis. You can name the tools and explain when they helped and when they got in the way.
  • Experience designing complex user flows. You have mapped and designed multi-step journeys that involved edge cases, error states, branching logic, and real user needs. You understand that a flow is only as strong as its weakest moment.
  • A/B testing experience with real outcomes. You have designed experiments, not just handed off screens. You have seen results, updated your assumptions, and made better decisions because of it.
  • Data-informed decision making. You use quantitative signals such as drop-off rates, conversion data, task completion, alongside qualitative research. You can show work where data changed what you built.
  • Inclusive design as a practice, not a principle. You have made specific decisions to serve users with different abilities, contexts, or literacy levels. You can talk about what you chose and why.
  • Figma fluency. Component architecture, auto layout, variables, and design tokens at a level that makes engineer handoff smooth.

Responsibilities

  • AI-assisted user flows: Design interfaces that surface machine learning outputs — recommendations, flags, automated decisions — in ways that feel clear and trustworthy, not overwhelming or opaque.
  • Complex multi-step flows: Own end-to-end journeys with many moving parts: onboarding, verification, financial decisions, settings. Map the full picture before you design any single screen.
  • Rapid AI-powered prototyping: Use tools like Figma AI, Galileo, Uizard, Framer, or similar to move from idea to testable prototype quickly. Know when a lo-fi sketch is enough and when a high-fidelity prototype earns its weight.
  • A/B testing and experimentation: Design variants with clear hypotheses. Work with product and data to interpret results. Let evidence guide your next iteration — not assumptions.
  • Conversational and voice UX: Design for chat-based and voice entry points where structure, language, and flow clarity matter more than visual polish.
  • Accessible and inclusive design: Build for users across geographies, languages, literacy levels, and abilities. Accessibility is structural here — not a final audit.
  • Design system contribution: Create and maintain components that scale without fragmenting. Your work should make the next designer's job easier.
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