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Browse remote LlamaIndex positions — RAG pipeline engineering, document intelligence, and LLM retrieval system development at AI-first companies.
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We operate a global content platform used by 20 million people across 30+ countries. Search is one of our most important product surfaces — and honest...
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Posted 6 months ago
Applications closedSolaria Data
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We want to build an AI agent that handles our end-to-end sales intelligence workflow — researching prospects, writing personalised outreach, updating...
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Role guide
LlamaIndex is the go-to framework for building RAG systems and document intelligence applications. Remote LlamaIndex jobs involve designing retrieval pipelines, connecting LLMs to private knowledge bases, and building production systems that answer questions accurately over large document corpora. These roles require deep understanding of chunking strategies, embedding models, and retrieval evaluation.
What is the difference between LlamaIndex and LangChain for remote jobs?
LlamaIndex specialises in document retrieval and RAG pipelines. LangChain is broader — covering agents, chains, and general LLM orchestration. Many companies use both. Job listings often list both as desirable.
Do LlamaIndex jobs require vector database experience?
Almost always. Pinecone, Weaviate, Chroma, and pgvector are the most common. Understanding how embedding similarity search works is essential for RAG engineering roles.
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