Product Engineer Intern at ThirdLayer (W25)
$30 - $60  •  
Building Dex, the AI Browser Copilot
San Francisco, CA, US
Internship
US citizen/visa only
About ThirdLayer

Dex is Cursor for everyday operations.

We’re reimagining the browser as an intelligent workspace—one that understands what you’re doing and helps you do it faster. Instead of static pages and disconnected apps, Dex adds a layer of context-aware AI that works with you in real time.

We’re a small, fast-moving team, with 7-figure backing from top-tier investors, solving one of the most fundamental problems in computing: how humans and computers work together.

About the role
Skills: Tailwind, Figma

This isn't just about building features. You'll work directly with the founding team to shape core user experiences, from conception to implementation. Whether it's prototyping agent interaction interfaces for or refining internal tools, you'll work at the intersection of design, engineering, and strategy.

What You'll Build

  • Elegant UIs using React/Next.js.
  • Interaction models for agent memory, delegation, and correction.
  • Internal tools/trackers for bug and feature requests.
  • Clean and modular documentation and engineering workflows.

Requirements

  • Experience with React/Next.js and TypeScript.
  • Experience building and shipping products to users.
  • Familiarity with design systems like Figma or Framer.
  • Project management experience with Linear, Notion, and/or Jira.
  • Preferred: Strong UI/UX or design portfolio.

Sample Projects

  • Designing intuitive interfaces for how users should delegate and override AI actions.
  • Create and manage Internal tooling to track recurring bugs and feature requests.
  • Interview users to determine feature priorities and product roadmap.
Technology

Existing approaches—like computer-use data and Model Context Protocols—still overlook a fundamental element: a deep understanding of how individuals actually use software.

Every person navigates their workday with unique mental models and personal systems for interacting with platforms and staying organized. These invisible frameworks shape productivity and workflow in ways that generic data can’t capture.

How can we systematically capture, structure, and teach these personal workflows to AI—enabling it to become a truly proactive, personalized extension of each user?

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