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Remote RAG Engineering Jobs
Browse remote RAG positions — retrieval-augmented generation pipeline development, vector search engineering, and document AI roles at companies building knowledge-intensive LLM products.
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At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developer...
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At LangChain, our mission is to make intelligent agents ubiquitous. We build the foundation for agent engineering in the real world, helping developer...
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Our mission is to reinvent the way people learn, starting with language. Learning a language can change a life by opening doors to new cultures, caree...
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Sierra is the leading platform for customer-facing AI agents, working with many of the world's biggest brands — including The GAP, Rocket Mortgage, So...
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Posted 2 months ago
Member of Technical Staff (Machine Learning Engineer, Search)
Perplexity
Belgrade
Perplexity is seeking an experienced Machine Learning Engineer to help build the next generation of advanced search technologies, with a focus on retr...
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Posted 2 months ago
Forward Deployed Engineer, Agentic Platform
Cohere
Middle East · also open in 1 other location
Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Who are we? Cohere is the leading security-first enterprise AI company. We build cutting-edge foundation AI models and end-to-end products that are de...
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Role guide
What to expect in remote RAG jobs
RAG (Retrieval-Augmented Generation) has become one of the most in-demand specialisations in AI engineering. Remote RAG jobs involve designing retrieval pipelines that combine vector search with LLM generation — reducing hallucinations and grounding responses in verified data. Engineers who master chunking, re-ranking, and retrieval evaluation are consistently in demand.
What you'll work on
- Design end-to-end RAG pipelines for enterprise knowledge base Q&A systems
- Optimise chunking strategies and embedding models for retrieval accuracy
- Implement re-ranking and hybrid search to improve RAG response quality
- Build evaluation pipelines that measure faithfulness, relevance, and groundedness
What companies look for
- End-to-end RAG pipeline design — ingestion, chunking, embedding, retrieval, generation
- Vector store integration (Pinecone, Weaviate, pgvector, Chroma)
- RAG evaluation frameworks — RAGAS, TruLens, or custom scoring pipelines
Frequently asked questions
What remote RAG engineering jobs are available?
RAG engineer roles, LLM retrieval specialists, and document AI developers. Most require Python, LangChain or LlamaIndex experience, and familiarity with at least one vector database.
Is RAG experience enough for LLM engineering jobs?
RAG is a strong specialisation, but most companies also expect broader LLM engineering skills — prompt design, evaluation, API integration, and Python production engineering alongside RAG expertise.
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