AI Azure Cloud & Generative AI Engineer

Professional Summary

AI Azure Cloud Engineer with 1 year of experience in designing, deploying, and automating cloud-native solutions on Microsoft Azure

Experienced in developing Generative AI applications using Azure OpenAI Service, Azure AI Search, Retrieval-Augmented Generation (RAG), FastAPI, and Python

Skilled in deploying and managing Azure services including Azure Virtual Machines, App Services, Azure Functions, Azure Kubernetes Service (AKS), Azure Storage, and Azure SQL Database

Proficient in Infrastructure as Code (IaC) using Terraform and ARM Templates, with hands-on experience automating cloud infrastructure deployments

Hands-on experience with Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG), vector embeddings, and Azure OpenAI Service to develop intelligent enterprise AI applications

Strong experience building and maintaining CI/CD pipelines using Azure DevOps, GitHub Actions, Git, Docker, and Kubernetes for reliable application delivery

Hands-on experience implementing Azure networking, cloud security, monitoring, and observability using VNet, NSG, Azure Key Vault, Azure Monitor, Log Analytics, and Application Insights

Proficient in Python, PowerShell, Bash, SQL, and FastAPI for cloud automation, infrastructure management, and AI application development

Passionate about delivering secure, scalable, and AI-powered cloud solutions while collaborating in Agile environments to drive digital transformation

Technical Skillsets

Cloud Platform: Microsoft Azure

Compute: Azure VMs, App Services, Azure Functions, AKS

Databases: Azure SQL Database, Cosmos DB, SQL

AI & ML: Azure AI Services, Azure Machine Learning (Azure ML), Azure OpenAI, Azure Cognitive Services, Large Language Models (LLMs), Prompt Engineering, Retrieval-Augmented Generation (RAG)

Programming: Python, Bash, PowerShell, SQL, FastAPI

DevOps: Azure DevOps, Git, GitHub, GitHub Actions, Azure Pipelines

Infrastructure as Code (IaC): Terraform, ARM Templates, Bicep

Containers: Docker, Kubernetes

Networking: Virtual Network (VNet), Network Security Groups (NSG), Load Balancer, VPN Gateway

Monitoring & Observability: Azure Monitor, Log Analytics, Application Insights

Work Experience

AI Engineer - Cloud Hrud. AI, India Jan 2026 – Till Date

Developed and deployed AI-powered applications using Azure OpenAI Service, Azure AI Search, FastAPI, and Python to deliver context-aware responses from enterprise knowledge bases

Designed and implemented Retrieval-Augmented Generation (RAG) pipelines integrating Azure AI Search, Blob Storage, embeddings, and Azure OpenAI for grounded AI responses

Automated Azure infrastructure provisioning using Terraform, reducing manual deployment effort by 60% and improving deployment consistency

Built and maintained CI/CD pipelines using Azure DevOps and GitHub Actions, reducing application deployment time by 40%

Containerized AI and Python applications using Docker and deployed workloads on Azure Kubernetes Service (AKS) and Azure Container Registry

Developed automation scripts using Python, PowerShell, and Bash for resource provisioning, application deployment, monitoring, and operational maintenance

Configured Azure networking components including Virtual Networks (VNet), Network Security Groups (NSG), Load Balancers, Private Endpoints, and VPN Gateway to ensure secure connectivity

Implemented cloud monitoring and alerting using Azure Monitor, Log Analytics, Application Insights, and Azure Alerts for proactive incident detection

Projects

1. Cloud Cost Optimization & Monitoring Dashboard

Technologies:

Azure Monitor, Log Analytics, Azure Resource Graph, PowerShell, Azure Functions, Azure SQL Database, Azure Dashboards

Developed a cloud monitoring and cost optimization dashboard to collect Azure resource metrics and identify underutilized resources

Leveraged Azure Monitor, Log Analytics, and Azure Resource Graph to analyse resource utilization and generate cost optimization insights

Automated data collection and scheduled reporting using Azure Functions and PowerShell scripts.

Stored monitoring data in Azure SQL Database and visualized infrastructure health and spending trends through Azure Dashboards

Applied Azure monitoring and governance best practices to improve resource visibility and operational efficiency

2. Enterprise AI Knowledge Assistant (RAG)

Technologies:

Azure OpenAI, Azure AI Search, Azure Blob Storage, Azure AI Document Intelligence, Azure Functions, FastAPI, Azure App Service, Azure Monitor, GitHub Actions

Developed an enterprise Retrieval-Augmented Generation (RAG) chatbot capable of answering user queries from PDF, Word, and Excel documents

Implemented document ingestion, OCR, vector embeddings, semantic search, and Azure OpenAI to generate context-aware responses

Built REST APIs using FastAPI and deployed AI services on Azure App Service with Azure Functions for scalable document processing

3. Azure AI Document Processing Platform

Technologies: Azure AI Document Intelligence, Azure OpenAI, Azure Blob Storage, Azure Functions, FastAPI, Azure SQL Database, Azure App Service

Developed an AI-powered document processing solution to extract structured information from invoices, forms, and business documents

Integrated Azure AI Document Intelligence for OCR, field extraction, and document classification

Used Azure OpenAI to summarize extracted content and validate document information

Automated document ingestion and processing using Azure Functions and Azure Blob Storage triggers

Education

Bachelors in AI&ML Malla Reddy Engineering College for Women Sep 2021 – May 2025

Vaishnavi Sangepu

AI Engineer Azure Cloud Engineer DevOps Engineer

Address: Hyderabad, India LinkedIn: https://www.linkedin.com/in/sangepuvaishnavi/

Cell: +91-707******* E-mail: *****************@*****.***

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