RAG Engineers + AI Developers

📋 Description

• Design and develop end-to-end RAG pipelines covering document ingestion, OCR processing, semantic
• Build and optimize vector and hybrid search solutions using technologies such as Pinecone, Qdrant
• Implement advanced retrieval strategies, including query rewriting, multi-query expansion, hybrid
• Develop robust document processing and knowledge ingestion workflows capable of handling complex
• Integrate RAG and retrieval components into customer-facing conversational interfaces, enterprise
• Establish automated evaluation and benchmarking frameworks to measure retrieval performance

🎯 Requirements

• 3+ years of hands-on experience developing production-grade RAG systems, semantic search solutions
• Strong commercial experience working with vector databases and modern embedding models, with
• Strong Python development skills and experience with frameworks such as LangChain, LlamaIndex, or
• Solid understanding of Large Language Models, embeddings, semantic search, information retrieval
• Experience implementing and evaluating advanced retrieval techniques such as query expansion
• Strong analytical and problem-solving skills, particularly in evaluating retrieval quality

🎁 Benefits

• Annual compensation of approximately INR 2,400,000–3,800,000 CTC, depending on experience and
• Full-time employment opportunity.
• Remote-friendly working model with flexibility across India.
• Opportunity to work on advanced AI, RAG, semantic search, and enterprise knowledge systems.
• Exposure to modern AI frameworks, vector databases, Large Language Models, and retrieval
• Location flexibility including Bangalore, Pune, hybrid, or remote across India.