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Niche LLM skills but mid-level Bangalore role and moderate brand result in medium competition.
Core LLM and ML skills transfer across industries despite fintech context.
Explicit 5+ years plus mandatory LLM, RAG, vector DB and tool experience makes shortlisting strictness high.
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Develop and optimize AI/ML and Generative AI solutions, focusing on Large Language Models (LLMs) and prompt engineering.
Design and implement Retrieval-Augmented Generation (RAG) pipelines, including chunking strategies, embeddings optimization, and advanced retrieval techniques.
Build and enhance chatbot, conversational AI systems, and enterprise Q&A assistants integrating vector databases and related AI orchestration frameworks.
Bachelor’s or Master’s degree in Computer Science, Data Science, Artificial Intelligence, or related field.
Minimum 5 years of overall IT experience with at least 3 years hands-on experience in AI/ML, Generative AI, or LLM-based solution development.
Strong proficiency in Python; knowledge of Java or similar technologies is a plus.
Experience with Large Language Models, prompt engineering, RAG pipelines, vector databases (Pinecone, Weaviate, FAISS, Milvus), and AI orchestration tools (LangChain, LangGraph, LlamaIndex).
Experienced in end-to-end development and optimization of AI-driven knowledge applications using LLMs and RAG techniques.
Comfortable integrating AI models with vector databases and conversational platforms, including chatbot and enterprise Q&A systems.
Technical capability to work with AI orchestration frameworks and implement advanced natural language querying and document extraction workflows.