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 up-to-date 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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