This is an Individual Contributor (IC) role. You'll lead through craft and what you ship — not people management.
We're hiring a product designer who can design polished UX and build production frontend experiences with AI coding tools and our design system. You'll take product problems from idea to spec, from spec to interface, and from interface to working PR.
Why This Matters
The handoff is broken. Design â spec â engineering queue â sprint â build â realise the design didn't survive contact with reality â repeat. That loop takes months and loses quality at every step.
We're betting on a different model: designers with deep craft who build directly, using AI as their engineering partner and a design system as their guarantee of quality. The design system makes AI-built UI consistent; your judgment makes it good.
The Challenge
You're a designer who ships. Not a designer who only hands off Figma files, not a frontend engineer waiting for a spec, not a PM writing documents about products. You hold the whole thing: the human-centred design thinking, the UI craft, and the build.
Your workflow looks like this: you take a product problem, sharpen the spec with AI, design the experience, then build the frontend yourself — with AI coding tools such as Claude Code, Cursor, Codex, or similar — using our design system's NPM packages, and open the PR. Idea to working product, one person, days not quarters.
And you don't just consume the design system. You help make it AI-native: the component APIs, design tokens, examples, agent instructions, MCP-style integrations, and documentation that help AI tools build on-brand, accessible UI by default.
Why Deriv
You'll join a culture that shares openly. Deriv is where we write about what we're shipping, what breaks, and what we figured out the hard way.
What You’ll Do
Design like a craftsperson
Ship the frontend yourself
Make the design system AI-native
Compress the loop
Who You Are
You have serious design craft. You have 4+ years in product design, with work that demonstrates deep UX thinking and refined UI execution. You can defend every decision in a screen — and you notice when something is 2px off.
You build what you design. You're fluent with AI-assisted coding tools such as Claude Code, Cursor, Codex, or similar. You're comfortable with React/TypeScript at component-composition level and at home in GitHub. You don't need to be a senior engineer — you need to ship working frontend experiences.
You can show proof of build. You have a link, repo, Loom, prototype, or shipped product that proves you personally designed and built something, ideally with AI tooling.
You spec with AI fluently. You use LLMs to sharpen thinking, not replace it — turning ambiguity into clear specs, exploring variations fast, and knowing when the model is confidently wrong.
You own outcomes. When the build breaks, you debug it. When AI output drifts off-system, you help fix the system so it doesn't happen again. You act as if company success is your personal responsibility.
Bonus Points
You think in systems. You understand design systems from both sides: as a consumer building products with them, and as an architect making them usable by humans and AI agents alike.
You've worked with design-system implementation. Tokens, component APIs, Storybook, package documentation, usage guidelines, or contribution workflows are familiar territory.
You've explored AI-native product or design-system workflows. Agent instructions, MCP-style integrations, AI coding agents, or structured documentation for AI tools are a plus — but we don't expect everyone to know our exact vocabulary yet.
Tech stack
Design: Figma, human-centred design methods.
Build: AI coding tools such as Claude Code, Cursor, Codex, or similar; React/TypeScript; GitHub.
System: Design system NPM packages, design tokens, component documentation, agent instructions, MCP-style integrations.
Ops: ClickUp, Slack.
The Honest Reality
This role is demanding because the ownership is real. You own the design, the build, and the outcome. You'll sometimes ship at 80% polish because validated learning beats perfect craft — and that may hurt, because you care about craft.
You'll debug AI-generated code that almost works. You'll write documentation so agents stop making the same mistake. You'll be one of the few people in the room who understands both the design question and the technical answer.
If you want a clean lane — pure designer, pure engineer — this isn't it. If you want to be the person who designs the product, builds it, and shapes the system that makes it all scale, it might be exactly your kind of role.