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Find freelance, contract, and remote opportunities involving retrieval-augmented generation, vector databases, embeddings, semantic search, and knowledge retrieval systems for AI applications.

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Latest RAG & Vector Database Setup Jobs

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Senior RAG & Vector Database Setup Expert

Remote• Contract•Just now
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Senior RAG & Vector Database Setup Expert

Remote• Contract•Just now
R

Senior RAG & Vector Database Setup Expert

Remote• Contract•Just now
R

Senior RAG & Vector Database Setup Expert

Remote• Contract•Just now
R

Senior RAG & Vector Database Setup Expert

Remote• Contract•Just now
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Opportunities

Latest RAG & Vector Database Jobs

Find projects focused on connecting AI applications with private or structured information. Opportunities include building RAG pipelines, generating embeddings, configuring vector databases, implementing semantic search, improving retrieval quality, and connecting knowledge sources to language models.

Find RAG Projects Built Around Real Data

Building useful AI applications often requires more than connecting an LLM to a prompt. Businesses need reliable ways to index, retrieve, and use their own information. Scoutance helps surface projects involving RAG architecture, vector search, embeddings, and knowledge retrieval, tailored to your technical experience.

Benefits

  • RAG and vector database opportunities from 50+ sources
  • Find projects involving embeddings and semantic search
  • Identify knowledge retrieval and AI search work
  • Match opportunities to your AI development skills
  • Receive project alerts through email and Slack


FAQ

Questions, answered

What types of RAG development projects can I find?
Projects can involve building retrieval pipelines, connecting document repositories to LLM applications, improving search and retrieval, implementing knowledge assistants, creating document Q&A systems, and integrating external information sources.
Can I find projects involving vector databases?
Yes. Opportunities may require setting up or managing vector databases to store and retrieve embeddings. Requirements vary by project and can include database configuration, indexing, similarity search, optimization, and integration with AI applications.
Are embedding and semantic search projects included?
Yes. Some projects focus specifically on converting information into embeddings and retrieving relevant content through semantic or similarity-based search. Scoutance can surface these opportunities when the required skills match your profile.
Do RAG projects require LLM development experience?
Many RAG implementations involve working with language models, but the required expertise varies. Some projects focus primarily on data pipelines, retrieval infrastructure, embeddings, or database configuration, while others require broader LLM application development skills.
How does Scoutance help me find specialized RAG opportunities?
Scoutance monitors 50+ sources and evaluates available projects against the skills, experience, technologies, and services in your profile. Relevant opportunities can be delivered through email and Slack, reducing the need to manually search across multiple platforms.

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Let Scoutance monitor multiple sources for RAG, vector search, and AI knowledge-system projects that fit your capabilities. Spend less time searching for specialized work and more time reviewing opportunities that match your technical background.

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