AI / Machine Learning Engineer

About RoleColorFinder™

RoleColorFinder™ is a fast-growing leadership development and personality-mapping platform that helps schools, organizations, and individuals discover their natural leadership colors. We combine psychology, design, and data to build systems that develop adaptable, values-driven leaders for the future.

The Role

We’re looking for an AI / Machine Learning Engineer to build the intelligence layer behind the RoleColorFinder leadership engine. You’ll work on everything from prompt engineering and model orchestration to embeddings, vector search, and our AI-driven Slack assistant. Your work will directly shape how users experience personalized insights, coaching, and leadership recommendations.

This is an unpaid, part-time, equity-only role at this stage. This role is perfect for someone who loves rapid experimentation, working across multiple layers of the AI stack, and building features that ship fast.

Responsibilities

• Develop prompt pipelines, agents, and lightweight models
• Build personalized leadership insight generation tools
• Implement embeddings and vector search within Supabase
• Power the AI-driven Slack assistant and reasoning workflows
• Create internal tools for automated summaries and analytics
• Iterate quickly, test outputs, and optimize for reliability and clarity

Requirements

• Solid understanding of LLMs, prompt engineering, and OpenAI API usage
• Experience with Python or JavaScript
• Bonus: LangChain, embeddings, Supabase vector search, agents, tool-calling workflows
• Ability to design systems that are reliable, testable, and predictable
• Comfort working in a fast-paced, early-stage environment

Commitment

• Flexible hours (part-time expectations)
• Fully remote, async-friendly
• High ownership over AI systems and experimentation

Compensation

• 0.01% equity
• Performance-based scale-up to 0.05%

Note: Although Wellfound requires this role to be listed as “Full-Time,” the actual workload is flexible and part-time in practice. We care about consistent communication and strong output, not strict scheduling.