About OpenLoop

OpenLoop was co-founded by CEO, Dr. Jon Lensing, and COO, Christian Williams, with the vision to bring care anywhere. Our telehealth support solutions are thoughtfully designed to streamline and simplify go-to-market care delivery for companies offering meaningful virtual support to patients across an expansive array of specialties, in all 50 states.

About the Role

As a Senior Product Designer, Design Systems at OpenLoop Health, you'll build the shared foundation that every OpenLoop product is designed and built on. That includes patient- and client-facing experiences, AI agents and copilots, and the operational platforms our teams use every day.

This role is for a systems designer who also understands AI. More of our UI is now generated by AI tools like Claude, Claude Code, and Figma Make, and those tools are only as good as the system they draw from. You don't just maintain a component library. You design tokens, components, and documentation that people and AI tools can both use correctly, and you write the skills and agent instructions that teach AI how to build with the system, so the right patterns show up by default.

You'll work closely with Product Designers, Engineers, and Product Managers across several product teams to set standards, not just document them.

What You'll Do

• Lead the design system end to end, from audit and roadmap through component design, documentation, release, and adoption
• Define and maintain a tiered token system (primitive, semantic, component) for color, type, spacing, elevation, and motion, including theming across the many client brands our White-Label platform supports
• Automate how tokens flow from Figma variables into code (e.g., Style Dictionary) so design and code stay in sync without manual handoff
• Build and maintain documentation that works like a product, with live examples, code snippets, and dos and don'ts, plus the AI skills and agent instructions that let designers, engineers, and AI agents apply the system correctly
• Make the system readable by AI agents through MCP servers, llms.txt-style docs, and component metadata, so agents build with the right components by default
• Prototype and test components in code using tools like Storybook, v0, Claude, or Claude Code to validate behavior against real implementation, not static mockups
• Define how components handle states, errors, edge cases, empty data, and accessibility, especially in clinical and operational workflows
• Partner with Engineers on quality: set acceptance criteria for components, review implementations, and use AI agents to catch drift between design and code