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Remote LlamaIndex Jobs
Browse remote LlamaIndex positions — RAG pipeline engineering, document intelligence, and LLM retrieval system development at AI-first companies.
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Posted 3 weeks ago
Senior AI/ML Architect, Applied Field Engineering/Field CTO
Snowflake
SG-Singapore
At Snowflake, we are powering the era of the agentic enterprise. To usher in this new era, we seek AI-native thinkers across every function who are en...
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Posted 3 weeks ago
Senior Software Engineer - Integrations - AI/ML
ClickHouse
Canada · also open in 4 other locations
The Connectors team is the bridge between ClickHouse and the broader ecosystem. We build and maintain the integrations that make ClickHouse accessible...
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Posted 1 month ago
Forward Deployed Engineer, Enterprise
Tavily
London, United Kingdom; Remote - Europe
Forward Deployed Engineering owns how Tavily shows up technically in the field. The team sits at the intersection of customers, Product, Engineering,...
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Join us and help shape the future of AI by defining the narrative around document understanding. We are looking for an AI Research Engineer to join ou...
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Join us and help shape the future of AI by defining the narrative around document understanding. LlamaIndex's backend application platform team is hir...
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Posted 4 weeks ago
Applications closedAI Earnings Call Signal Extraction Engineer
Quelion Intelligence
On-site
New York, United States (UTC-5)
Quelion Intelligence builds research tools for hedge funds and asset managers. Every quarter, thousands of earnings calls happen in a span of a few we...
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Posted 4 weeks ago
Applications closedSenior AI Contract Obligation Tracking Engineer
Selvix Works
Remote
New York, United States (UTC-5)
Signed contracts don't end when the ink dries. Renewal windows, price escalators, audit rights and notice periods sit buried in thousands of PDFs, and...
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Posted 4 weeks ago
Applications closedAI Docs Search RAG Engineer
Yentrix Works
Remote
Sao Paulo, Brazil (UTC-3)
LlamaIndex, OpenAI embeddings, FastAPI and a Postgres-backed vector index sit underneath the 'Ask the docs' widget that runs on 450 developer document...
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Posted 4 weeks ago
Applications closedJunior AI Regulatory Obligation Tagging Analyst
Delvio Solutions
Remote
New York, United States (UTC-5)
We work async across six time zones, and we trust juniors with real responsibility from week one. Delvio Solutions helps compliance teams track what n...
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Posted 4 weeks ago
Applications closedSenior AI Data Lineage Inference Engineer
Lyrex Data
Remote
Berlin, Germany (UTC+1)
You'll join a platform team of eight engineers and one designer who own our data catalog product end to end. The catalog already ingests metadata from...
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Role guide
What to expect in remote LlamaIndex jobs
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 you'll work on
- Build RAG systems that answer questions over enterprise knowledge bases and documents
- Design multi-document retrieval pipelines with re-ranking for accuracy
- Create agents that query structured and unstructured data sources with LlamaIndex
- Develop evaluation pipelines to measure retrieval and generation quality
What companies look for
- LlamaIndex core abstractions — nodes, indices, query engines, retrievers
- Chunking strategy design and embedding model selection for retrieval quality
- Integration with vector stores (Pinecone, Weaviate, pgvector) and LLM APIs
Frequently asked questions
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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