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Senior UX designer (AI)

Norton Blakelondon, england🇬🇧United KingdomPosted 19 Sept 2026

Why This Role Stands Out

You'll have the opportunity to shape the future of AI-powered experiences and innovate within a reputable company, leveraging your coding and design skills in a hybrid setting with a competitive daily rate. This role is perfect for a technically adept UX designer who thrives on building functional prototypes and collaborating across diverse teams to drive cutting-edge AI integration. Apply now to be at the forefront of AI design!

Quick Overview

Seniority
Mid Senior
Work mode
Hybrid
Location
london, england, United Kingdom
FigmaCSSHTMLJavaScriptReact

Job Description

UX designer (AI), 3 months, London/Hybrid, £425/day (Inside IR35)

The role in one line

A designer who codes (or an engineer who designs) to act as the catalyst for the client's new AI Community of Practice — prototyping AI-powered experiences in working code, and embedding AI into how the design teams themselves work.

What they’ll actually do

  • Design interactions for AI-driven products: chat, generative tools, recommendation systems, agentic flows
  • Build high-fidelity coded prototypes in React to test concepts with real customers
  • Use AI tooling (Figma, Cursor, Kiro, Claude Code, custom plugins) to prototype and iterate at speed
  • Build reusable AI pattern components — prompt inputs, chat, data visualisation, agent workflows — aligned to the existing design system
  • Work across engineers, architects and data scientists, and bring their workflows into the design practice
  • Explain technical trade-offs to non-technical stakeholders

Non-negotiables — screen hard on these

  1. A portfolio of live, coded prototypes. Not static Figma files, not case-study write-ups. Shipped AI features preferred.
  2. JavaScript, HTML, modern responsive CSS, React. Hands-on and current.
  3. Advanced Figma. Variables, auto-layout, prototyping, design systems and tokens.
  4. MCP experience. Designing AI workflows that connect models to interfaces with context-aware data flow.
  5. Agent building or AI output evaluation. Practical, with a considered view on where AI falls short.

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