Member of Technical Staff (Software Engineer, Design System)
Perplexity is looking for a frontend engineer to build the design system behind every Perplexity product. It is the component library and design language shared across web, iOS, Android, macOS, and Windows – the primitives, tokens, and interaction patterns that every product team builds on top of.
Its users are internal, spanning product teams and a broad range of contributors across the company. The components you build become the foundation all of them rely on. You will develop component APIs that hold up across dozens of consuming surfaces and are easy for other teams to adopt correctly, contribute to the token pipeline that keeps five platforms visually consistent, and maintain a high bar for interaction quality and accessibility.
Tech Stack: React · TypeScript · CSS · Design Tokens
What you'll do
- Design and build core primitives – overlays, inputs, navigation, feedback – with APIs that stay coherent as consumers multiply
- Work across the design-token pipeline – authoring, generation, and per-platform publishing across web, iOS, Android, macOS, and Windows
- Partner directly with design on the design language itself, translating Figma systems into typed, testable, documented components
- Migrate product surfaces off bespoke implementations onto shared primitives without breaking them
- Build accessible components by default – keyboard, focus, contrast, screen readers – backed by automated coverage
- Support consuming teams through docs, visual regression coverage, and on-call rotation
What we're looking for
- 4+ years building production frontend; experience with a design system, component library, or shared UI platform is a plus
- Interest in building reusable components
- Strong React and TypeScript, and CSS
- Working accessibility knowledge (WCAG, ARIA patterns, assistive tech)
- Comfort collaborating closely with designers on the visual and interaction language
About Perplexity AI
Perplexity AI is an AI-chat-based conversational search engine that delivers answers to questions using language models.
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