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About the role
Role & Responsibilities - Design, develop, and deploy enterprise-grade LLM (Large Language Model) and RAG (Retrieval-Augmented Generation) solutions. - Build scalable AI applications using Python and modern GenAI frameworks. - Develop and optimize prompt engineering, retrieval pipelines, and vector search implementations. - Integrate LLMs with enterprise knowledge bases, APIs, and data platforms. - Collaborate with cross-functional teams to translate business requirements into AI-driven solutions. - Monitor, evaluate, and improve the performance, accuracy, and reliability of AI models. - Drive best practices in AI architecture, code quality, and deployment. - Mentor team members and stay updated with the latest advancements in Generative AI technologies. Preferred Candidate Profile - Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field. - 615+ years of experience in Software Engineering, AI/ML, or Data Engineering. - Hands-on experience with LLMs, RAG Architecture, Prompt Engineering, Python, LangChain/LlamaIndex, Vector Databases (FAISS, Pinecone, ChromaDB), and SQL. - Experience with cloud platforms such as Azure, AWS, or GCP. - Solid understanding of NLP, Machine Learning, and Generative AI concepts. - Excellent analytical, problem-solving, stakeholder management, and communication skills. .
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