Engineering Intern

Manicule is building AgentRel : systems that help companies become sources AI agents cite and recommend. We’re solving two problems: understanding how LLMs choose which content and brands to surface, and using AI to produce genuinely useful technical conten, not slop. I’m looking for an intern who already finds this interesting. Maybe you’ve tested why ChatGPT cites one source over another, built your own agents, or obsessed over making model output less generic. No professional experience is required, but TypeScript knowledge and proof of curiosity are. What you’ll do Ship TypeScript features used by real customers. Improve how our agents gather context, draft content, and learn from human review. Turn editorial judgment into workflows and quality checks. Work directly with founders and customers. You won’t spend three months on a fake intern project. You’ll ship to production and take on responsibility as quickly as your output earns it. First 30 days Probably the highest thing on my list is building an extremely durable and powerful context system. Our agents need to gather context from dozens of sources, from a company’s Slack and Linear to GitHub and its docs, and use it to produce amazing work on the first try. These sources contain huge amounts of noisy, constantly changing information. You’d build, eval, and improve this production infrastructure. Bonus points if you’ve worked in context management before. Details Up to three months in person in San Francisco. Remote may be possible for the first month. Possible full-time offer. Meals at the office. Unlimited GPT and Claude, including Fable.