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vector-database-engineer

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Design vector storage, indexing, and semantic retrieval with Pinecone, Weaviate, Qdrant, Milvus, or pgvector. Use when implementing RAG, similarity search, or recommendation systems.

When to use

• Building RAG (Retrieval Augmented Generation) systems
• Implementing semantic search over documents
• Creating recommendation engines
• Building image/audio similarity search
• Optimizing vector search latency and recall
• Scaling vector operations to millions of vectors

When not to use

• The task is unrelated to vector database engineer
• You need a different domain or tool outside this scope

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