Retrieval-Augmented Generation (RAG) Engineer

Seeking a RAG Engineer to build AI applications that combine enterprise knowledge retrieval with Large Language Models.

Responsibilities:

• Design and develop RAG pipelines.
• Build document ingestion and processing pipelines.
• Implement chunking and embedding strategies.
• Configure vector and hybrid search.
• Integrate LLMs with enterprise knowledge bases.
• Optimize retrieval accuracy.
• Implement reranking and metadata filtering.
• Evaluate RAG performance.
• Develop production APIs and services.

Required Skills:

• RAG.
• LLMs.
• Python.
• Embeddings.
• Vector databases.
• Pinecone/Weaviate/Qdrant/FAISS/Chroma or equivalent.
• Elasticsearch/OpenSearch preferred.
• LangChain/LlamaIndex.
• REST APIs.
• Cloud platforms.