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The ideal candidate will have hands-on experience in designing and deploying LLM-powered applications, building RAG pipelines, fine-tuning models using LoRA/Quantization, and implementing multi-agent workflows. If you're passionate about building intelligent systems that power real-world educational and analytical tools, this is your opportunity to innovate with us. Shift : Day shift ( 10 am - 7 pm) Monday to FridayKey\nResponsibilities: Build and optimize LLM-based applications using frameworks like LangChain, Hugging Face, CrewAI, LangGraph, and LlamaIndex. Develop and maintain RAG (Retrieval-Augmented Generation) pipelines using vector databases like Pinecone, Astra DB, Chroma to improve retrieval accuracy. Fine-tune models (e.g., Llama3, Mistral) using techniques such as LoRA, Quantization, and PEFT to enhance performance and reduce latency. Design agentic AI systems using multi-agent coordination strategies for tasks such as automated content generation and evaluation. 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