AI Engineer - Azure AI Foundry, Azure Open AI, RAG, LLM

Role AI Engineer, Azure AI Location Greater Noida, Pune Experience 8+ yrs Key Responsibilities AI & GenAI Solution Development Design, develop, and deploy AI/ML and GenAI solutions using Python and Azure AI services. Build applications using Large Language Models (LLMs), including prompt engineering, RAG (Retrieval Augmented Generation), fine-tuning, and orchestration. Integrate LLMs into enterprise workflows, applications, and platforms. Azure AI & MLOps Work extensively with Azure OpenAI, Azure AI Studio, Azure ML, Cognitive Services, and related Azure services. Ensure scalability, performance, security, and cost optimization of AI workloads on Azure. Engineering & Integration Develop clean, scalable, and well-documented Python code for AI services and APIs. Integrate AI solutions with existing enterprise systems, data platforms, and applications. Collaborate with data engineering teams on data pipelines, feature stores, and model inputs. Governance, Security & Responsible AI Implement responsible AI principles including explainability, bias mitigation, data privacy, and security. Ensure compliance with organizational AI governance, risk, and regulatory requirements. Monitor model performance, drift, and usage in production environments. Collaboration & Enablement Support multiple AI initiatives across business units as an SME. Provide technical guidance, best practices, and reusable AI components/frameworks. Participate in architecture reviews, design discussions, and technical decision-making. Required Skills & Qualifications Technical Skills Strong handson experience with Python for AI/ML development. Solid experience working on Azure cloud, including: Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure App Services / Functions / Containers (AKS, ACR) Practical experience with LLMs (OpenAI, Azure OpenAI, opensource models). Handson knowledge of prompt engineering, embeddings, vector databases, and RAG patterns. Experience building and consuming REST APIs for AI services. Familiarity with ML frameworks such as PyTorch, TensorFlow, Scikitlearn, or similar. Experience with CI/CD and MLOps tools. .