Shekhar Rangu

About Shekhar Rangu

Working as a.Net Full Stack Developer at AmeriHealth Caritas. As an enthusiastic programmer, I am eager to learn new technologies. I have around 8 years of work experience in the software industry.Backend Technologies: C#, Java, Python.Net Core, C, PHP, Microservice.Net MVC, Entity Framework Core.AI Skills: Retrieval Augmented Generation (RAG), Azure AI Search (Vector Search, Hybrid Search), Cognitive Search, Azure OpenAI Service (GPT, Embeddings), Azure AI Foundry, LangChain, LangGraphWeb Technologies: Angular, React, TypeScript, JavaScript, HTML, CSS, Bootstrap,JQuery, Ajax, JSON, Material.Databases: MS SQL, Oracle.Development Tools: Visual Studio, VS Code, SSMS, NetBeans, Eclipse.Version Controls: Git, GitLab and GitHub.DevOps & Cloud: Azure Devops, Azure App Services, Azure Functions, Azure Key Vault, Jenkins, GitLab, Git, CI/CD PipelinesTesting: Spec flow, Reqnroll Junit, xUnit, NUnit, Jasmine, Karma, Rest API RestingOther Tools: SoapUI, Bot Framework, Kubernetes, Docker, Postman, Swagger, Gitbash, Android Studio.

Experience

1. Software Engineer

   AmeriHealth Caritas

   Mar 2023 — Present · Charlotte, NC, US

   Developed applications using.NET Core backend and the latest Angular Material UI, delivering a responsive and intuitive user experience for policyholders and agents.• Followed Clean Architecture and Domain-Driven Design principles to build maintainable and scalable insurance modules, including quote, policy, document storage, and claims processing.• Implemented the Command-Query Responsibility Segregation (CQRS) pattern for clear separation of read and write operations, improving performance and maintainability.• Built the application using a microservices architecture, allowing modular deployment.• Collaborated in an Agile environment, participated in sprint planning, and defined user stories.• Deployed microservices on Azure Red Hat OpenShift, ensuring secure, scalable, and containerized cloud deployment.• Designed and developed an AI-powered chatbot leveraging Azure OpenAI, Azure AI Search, and Document Intelligence to enable intelligent document-based question answering.• Implemented Retrieval-Augmented Generation (RAG) architecture, combining Azure AI Search vector embeddings with OpenAI GPT models for accurate, context-aware responses.• Integrated Azure Blob Storage to securely store and retrieve user-uploaded documents such as PDFs, Word files, and policy documents for real-time querying.• Created custom Azure AI Search indexes containing both text and vector embeddings, enabling semantic and keyword-based retrieval from large document datasets.• Developed.NET Core backend APIs to handle document uploads, indexing, and chatbot interactions with seamless integration between storage, AI Search, and OpenAI services.

Education

• RGUKT Basar

  Pre-University Course (M.P.C)

  2012 — 2014

• ZPHS Thigul

  SSC

  2002 — 2012

• RGUKT Basar

  Bachelor of Technology (B.Tech.), Computer Science&Engineering

  2014 — 2018