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AI Docs Search RAG Engineer

Hunter Carvalho

Full-time · Job · Sao_Paulo

About the role

LlamaIndex, OpenAI embeddings, FastAPI and a Postgres-backed vector index sit underneath the 'Ask the docs' widget that runs on 450 developer documentation sites. Yentrix Works builds documentation tooling, and answering developer questions directly from docs is now our most-used feature. It's also our noisiest: outdated pages get cited, code samples get mangled and version-specific answers mix together. You'll own retrieval quality, from chunking and ranking to version awareness and citation accuracy.

Responsibilities

  • Own retrieval quality for our docs question-answering product
  • Improve chunking for code-heavy pages, tables and versioned content
  • Build an evaluation set from real user questions and track answer quality weekly
  • Partner with the frontend team on citations and feedback signals

Requirements

  • Production experience building RAG systems with real users
  • Strong Python and API skills (FastAPI a plus)
  • Hands-on with LlamaIndex, LangChain or a custom retrieval stack
  • Understands embeddings, rerankers and hybrid search trade-offs

Benefits

  • Remote across the Americas
  • Stock options
  • Health stipend adjusted to your country
  • Home office allowance and coworking budget

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Job Type

Full-time

Level

Mid-Level

Language

English

Salary Range

$100k – $130k / year

AI Expertise

NLP & Prompt Engineering AI & Machine Learning Engineers

Skills

python rag llamaindex openai api fastapi

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