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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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Posted 4 weeks ago
Applications closedQuilvex Systems
Hybrid
Chicago, United States (UTC-6)
We work with 14 regional property and casualty carriers, and their field adjusters spend nearly half of each claim on paperwork. Quilvex Systems build...
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Posted 1 month ago
Applications closedFelvix Tech
On-site
New York, United States (UTC-5)
We believe AI should make government more legible to the people it governs, not just to lobbyists who can afford to hire analysts. Our tools are alrea...
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Posted 1 month ago
Applications closedWevio Systems
Remote
Berlin, Germany (UTC+1)
We already have a strong embedded analytics product that surfaces dashboards inside client apps. What we don't have yet is a natural language layer th...
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Posted 1 month ago
Applications closedGradrix Works
Remote
London, United Kingdom (UTC+0)
As a fully async team spread across nine time zones, we believe great engineers can build great retrieval systems without ever sharing a timezone with...
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Posted 1 month ago
Applications closedLamion Solutions
Hybrid
Chicago, United States (UTC-6)
Clinical trial coordinators, hugging face models, and a growing library of eligibility criteria templates are what you'll work with daily. If you're e...
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Posted 1 month ago
Applications closedLontex Tech
Remote
Los Angeles, United States (UTC-8)
LangChain, custom retrievers, and a growing vector index are the backbone of our RAG stack. We need someone who can benchmark retrieval latency across...
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Posted 1 month ago
Applications closedDravix Studio
Remote
New York, United States (UTC-5)
We publish internally on prompt design patterns and encourage the team to share findings at audio-tech meetups, since a lot of what we learn generatin...
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Posted 1 month ago
Applications closedBrenvo Tech
Remote
Johannesburg, South Africa (UTC+2)
We don't care where you work from. We care about clear communication, steady output, and whether your prompt changes actually reduce chatbot escalatio...
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Posted 1 month ago
Applications closedOrvix Works
Remote
Mexico City, Mexico (UTC-6)
Our clients include procurement teams at mid-market manufacturers who are drowning in unstructured supplier emails, contract PDFs, and spend reports....
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Posted 1 month ago
Applications closedLontex Tech
Remote
Stockholm, Sweden (UTC+1)
PyTorch is nowhere near as central to what we build as our multi-agent orchestration layer is. If you've spent time chaining LLM agents together and w...
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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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