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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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Neo4j is the graph intelligence platform that transforms data into knowledge to power the next generation of intelligent applications and AI systems....
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Comet is building the development platform for teams who want to ship robust, reliable, and responsible AI applications. Opik, our open source LLM eva...
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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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Owkin is an agentic AI company pioneering Biological Artificial Superintelligence to solve problems in biology where human researchers alone have fail...
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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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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
Staff Applied AI Engineer - Enterprise AI Solutions
Snorkel AI
New York City, NY (Hybrid); San Francisco, CA (Hybrid); United States (Remote)
Snorkel AI is the frontier AI data lab, helping teams build the data and environments behind high-performing frontier and agentic AI. We combine techn...
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Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we've raised over $6...
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Unstructured is defining the standard for enterprise data transformation in the age of LLMs and generative AI. In just two years, we've raised over $6...
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We’re on a mission to make data available and actionable to everyone, everywhere. With 700+ connectors, our platform powers analytics and gives AI age...
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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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