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Role & responsibilities - Develop and enhance Generative AI applications using LLMs and AI frameworks. - Build and optimize RAG pipelines, vector search, and AI-powered workflows. - Design effective prompts and fine-tune models using techniques such as LoRA and QLoRA. - Develop REST APIs and integrate AI capabilities into enterprise applications. - Deploy, monitor, and maintain AI solutions in cloud and containerized environments. - Ensure code quality through testing, debugging, documentation, and code reviews. - Follow Responsible AI, security, and data governance practices. Preferred candidate profile - Strong proficiency in Python, OOP, APIs, debugging, and software development best practices. - Valuable understanding of Data Structures & Algorithms, complexity analysis, and problem-solving. - Hands-on experience with LLMs, Prompt Engineering, RAG, AI Agents, and embeddings. - Experience with LangChain, LangGraph, LlamaIndex, Hugging Face, or similar frameworks. - Knowledge of vector databases, semantic/hybrid search, and retrieval architectures. - Experience with PyTorch, TensorFlow, or Keras. - Familiarity with Docker, Git, CI/CD, and cloud platforms (Azure/AWS/GCP). - Understanding of AI governance, data privacy, and Responsible AI principles. .