Lunon
Founding Design Engineer
About this role
Lunon seeks a founding design engineer to build the platform interface for an AI-native consulting firm serving PE firms and enterprises. You'll own the full spectrum of design and engineering, creating high-fidelity interfaces for complex financial analysis that executives trust, while establishing the design system for future team growth.
What you'll do
- Design and build end-to-end platform interfaces for consulting engagements, from scoping through AI research to client deliverables
- Create data visualizations and interactions that make complex financial analysis clear and trustworthy for PE partners and executives
- Establish design system and frontend standards that scale with the team
- Ship features independently without handoffs, bridging design and engineering
- Evaluate and integrate emerging design and development tools to improve workflow
- Ensure every pixel and interaction meets the quality bar for high-stakes decision-making
What they're looking for
- Design engineering (prototyping and production code with equal fluency)
- Data visualization and complex UI design
- Frontend development (modern web frameworks)
- Design tools (Figma, Framer, or equivalent)
- Design taste and craft obsession
- Problem-solving across ambiguous startup challenges
- User empathy and communication
- Product thinking and systems design
Benefits
- Early equity in a category-defining company
- Small founding team with high trust and no bureaucracy
- $2,400 yearly learning and tools stipend
- Early access to OpenAI models through partnership
- Remote work
- No politics, direct building environment
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Lunon
Lunon builds an AI-native consulting platform designed for private equity firms and enterprises to conduct complex financial analysis. The company is hiring founding design engineers to create trusted executive interfaces and establish scalable design systems.
View all jobs at LunonLikely interview questions
- Walk us through a project where you designed and built something end-to-end yourself—what tools did you use, and how did you know when to iterate vs. ship?
- Tell us about a time you had to make a complex dataset or financial information understandable to non-technical stakeholders. How did you approach it?