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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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We are a Gulf retail bank. We want to deploy an AI chatbot that handles Tier-1 customer enquiries — balance checks, transaction history, card blocking...
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We have three automation projects that have been approved by leadership and need to get done. Budget is allocated. Timeline is 4 months. Project 1: Co...
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We're a small but fast-moving AI studio and we're looking for a Senior LLM Engineer to own the core of our language model stack. You'll work directly...
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We're a LegalTech startup building an AI system that extracts key clauses, obligations, and risks from commercial contracts. We need a prompt engineer...
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Posted 6 months ago
Applications closedSolaria Data
Remote
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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Posted 7 months ago
Applications closedCyberSense AI
Remote
We build contract analytics software. Our current NER pipeline was fine-tuned 2 years ago on a limited dataset and it's not keeping up with contract c...
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Posted 8 months ago
Applications closedMediaMind AI
Remote
E-commerce platform, 2M users across France, Germany, Spain and Italy. Our support volume is 60% repetitive questions — shipping times, return policie...
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Role guide
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 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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