C
RAG Pipeline Developer
Claire Dupont
Full-time · Mid-level · Los_Angeles
About the role
We are building a knowledge assistant for our internal teams and need a developer to design and implement the RAG (Retrieval-Augmented Generation) pipeline — from document ingestion to vector search to response generation.
Responsibilities
- Design and build the end-to-end RAG pipeline
- Implement document chunking, embedding, and indexing strategies
- Integrate with OpenAI or Anthropic for generation
- Build an evaluation framework for retrieval and answer quality
- Document the system for internal engineering team
Requirements
- Experience building RAG systems with LlamaIndex or LangChain
- Familiarity with vector databases (Pinecone, Chroma, Qdrant, Weaviate)
- Strong Python and understanding of embedding models
- Able to evaluate retrieval quality and improve relevance
- Comfort working with unstructured data (PDFs, Word docs, Confluence)
Benefits
- Greenfield RAG project — your design decisions
- Remote
- Equity
- Learning budget
- Small, smart team
Job Type
Full-time
Level
Mid-level
Language
English
Salary Range
$100,000 – $130,000
AI Expertise
NLP & Prompt Engineering
data science & analytics
data science
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