Sr. Full Stack AI Developer

We are looking for a passionate and experienced Senior AI Developer – Azure OpenAI with 5–8 years of experience in designing, developing, and deploying enterprise-grade AI-powered business applications. The ideal candidate should have strong expertise in Generative AI, Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), Azure OpenAI, and enterprise application development, along with a minimum of 2 years of hands-on experience in .NET technologies. As a Senior AI Developer, you will lead the design and development of scalable AI solutions, enterprise Copilots, intelligent automation platforms, and AI-powered applications using Microsoft Azure AI services. You will work closely with AI engineers, .NET developers, software architects, data teams, and business stakeholders to deliver secure, scalable, and high-performing AI solutions for real-world business problems. Key Responsibilities Design, develop, and deploy enterprise-grade Generative AI applications using Azure OpenAI Service, GPT models, and OpenAI APIs. Lead the development of AI-powered applications using Python and .NET technologies. Build enterprise AI assistants, chatbots, and Copilot-style solutions for business users. Design and implement scalable Retrieval-Augmented Generation (RAG) solutions for enterprise knowledge search and intelligent assistants. Develop intelligent document processing, summarization, automation, and workflow solutions. Build conversational AI applications using Large Language Models and foundation models. Work with Azure OpenAI, Azure AI Search, Azure AI Foundry, Azure Storage, and other Azure AI services. Design and develop backend services, APIs, and microservices using .NET/.NET Core, C#, Python, FastAPI, or Flask. Integrate AI capabilities with enterprise applications, web platforms, APIs, SharePoint, Microsoft Teams, and other business systems. Develop vector search and semantic search solutions using Azure AI Search or other vector databases. Build and optimize data ingestion pipelines for documents, PDFs, structured data, and enterprise knowledge repositories. Work with embeddings, document chunking, indexing, retrieval, reranking, and grounding mechanisms. Design effective prompts, system instructions, reusable prompt templates, and prompt engineering frameworks. Optimize LLM applications for response quality, token usage, latency, scalability, performance, and cost. Define and implement LLM evaluation strategies to continuously improve AI response quality and reliability. Implement guardrails, content filtering, hallucination control, Responsible AI practices, and secure AI application patterns. Design and develop REST APIs and microservices using ASP.NET Core, C#, FastAPI, Flask, or similar frameworks. Support secure AI solution architecture using Microsoft Entra ID, RBAC, Managed Identity, and Azure security best practices. Deploy and manage AI applications using Azure App Service, Azure Functions,…