Developed an end-to-end deployment blueprint for Retrieval Augmented Generation (RAG) workflows on Azure Kubernetes Service, focusing on the NVIDIA/nim-deploy repository. The work involved configuring cloud environments, installing the NVIDIA GPU Operator, and orchestrating Helm-based deployments to enable GPU-accelerated RAG solutions for enterprise data. Documented comprehensive access and testing procedures to support secure, scalable experimentation with generative AI in enterprise settings. Leveraged expertise in Azure, Kubernetes, and Helm, with supporting scripts in Bash and documentation in Markdown. The resulting guide provides a clear, reproducible path for deploying and validating RAG frontends, addressing enterprise requirements for cloud-native, GPU-enabled AI workflows.