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skabhishek/README.md

๐Ÿ‘‹

I am an Enterprise Cloud & Generative AI Solution Architect with over 17 years of experience building secure, multi-tenant B2B SaaS platforms and data engineering pipelines.

I specialize in Tenant-Isolated Generative AI architectures, helping enterprises leverage the power of LLMs directly inside their native cloud ecosystem without risking data leaks.


๐Ÿ› ๏ธ Core Technology Stack

  • AI & Agentic Orchestration: Python, Node, Semantic Kernel (.NET), Azure OpenAI, Azure AI Foundry, LangChain, LangGraph
  • Vector Storage & Search: Azure AI Search, PostgreSQL (pgvector), Azure Cosmos DB
  • Backend Ecosystem: .NET 8 / C# Core, ASP.NET Web API, Node.js, Express, Microservices
  • Frontend Development: React.js, Next.js, Redux, Modern JavaScript/TypeScript
  • Data Engineering: Microsoft Fabric, Fabric Lakehouses, PySpark, Azure Data Factory, Azure SQL Server
  • DevOps & Cloud Infra: Microsoft Azure, Pulumi (Infrastructure as Code), GitHub Actions, Docker

๐Ÿš€ Featured AI & Enterprise Repositories

A reference architecture for a multi-tenant knowledge retrieval platform. Built with .NET 8 and Semantic Kernel, it demonstrates strict document metadata filtering via Azure AI Search and pgvector to guarantee total data isolation across enterprise clients.

A production-ready starter template for orchestrating native C# AI agents. Includes concrete examples of structured JSON outputs, native plugin tool-calling (connecting LLMs to SQL databases), and systemic conversational memory management.

Automated multi-layer (Bronze โž” Silver โž” Gold) data ingestion templates optimized for Microsoft Fabric. Features highly parallelized PySpark transformations designed to flatten and optimize nested relational data footprints for real-time analytics.


๐Ÿ“ซ Connect & Collaborate

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