Gen AI

Develop and fine-tune Generative AI models using Azure OpenAI (GPT-4o, GPT-4o-mini, Embedding Models, etc.), NLP, and Large Language Models (LLMs).Implement and optimize AI solutions for text generation, document summarization, and predictive analytics.Leverage Prompt Engineering techniques to refine AI-generated responses for domain-specific applications.Enhance search capabilities using Azure AI Search(previously Cognitive Search) for intelligent data retrieval.Utilize Azure Document Intelligence(previously Form Recognizer) to automate document processing and structured data extraction.Optimize model performance through hyperparameter tuning, transfer learning, and fine-tuning techniques.Manage and process large-scale datasets using Azure Storage Containers for AI-driven applications.Leverage Redis Cache to enhance AI model response time and optimize application performance.Utilize Python for data preprocessing, feature engineering, and AI model development.Develop AI-driven applications with Python and cloud-based APIs.Deploy AI models and applications using Azure DevOps (CI/CD) pipelines for automated workflows.Integrate AI solutions with cloud-based infrastructures leveraging Azure services like Azure function apps and Azure OpenAI APIs.Ensure AI scalability and performance using containerized environments and cloud-native solutions.Hands-on experience with Azure AI services (OpenAI, AI Search, Document Intelligence).Knowledge of LLMs, Prompt Engineering, and Responsible AI practices.Familiarity with Redis Cache for optimizing AI inference times.Experience with MLOps and CI/CD best practices using Azure DevOps.Familiarity with all aspects of RAG framework from chunking strategies, embedding model selection, relevant system prompt tuning for RAG response, etc. Theoretical understanding of language models and the transformer architecture. Also familiarity with popular frameworks like Chain of Thought, ReAct framework for Agents