Unknown Company
About the Role
- Curate structured data signals from messy human input (e.g., interviews, resumes, calls, chat logs).
- Prototype LLM-based tools that automate real-world recruiting and matching tasks.
Responsibilities
- Build prompt pipelines, retrieval chains, and evaluation loops for our AI agents.
- Develop small internal tools that integrate with CRMs, Notion, and candidate workflows.
- Assist in building MVP experiments that turn into core product modules.
What We’re Looking For
- Strong interest in applied LLM development (OpenAI, Claude, LangChain, etc.).
- Proficiency in Python (bonus for JS/React experience).
- Experience or interest in tools like Pinecone, Weaviate, Chroma, Postgres, Supabase, or similar.
- Hands‑on with prompt engineering, data wrangling, and rapid prototyping.
- Understanding of how data pipelines, frontend, and product interact.
- Bonus: past projects in recruiting tech, productivity apps, or agent frameworks.
What You’ll Work On
- A candidate interview summarizer & intent extractor.
- An agent that researches talent signals from web sources (automated headhunter).
- A resume parser & recruiter assistant tool.
- Evaluation pipelines that score output relevance and impact.
Why Join Us
- Learn how to build LLM apps from 0→1 inside a real business use case.
- Build and ship fast with direct mentorship from the founding team (engineers + operators).
- Flexible hours, async work style, and real impact on product.
- Potential to convert into a Founding Engineer or AI Agent Engineer role after the internship.