From Full Stack .NET Developer to AI Engineer: The Complete 2026 Roadmap 🚀

Are you a C# or Full Stack .NET developer looking to level up your career into AI Engineering? 🚀 In this comprehensive roadmap guide, we break down step-by-step how .NET developers can transition into building enterprise-grade Large Language Model (LLM) applications and Retrieval-Augmented Generation (RAG) systems using C#. 🔥 What You'll Learn in This Video: • The transition path from traditional Full Stack .NET to AI Engineering • Core AI Orchestration with Microsoft Semantic Kernel & Kernel Memory • Managing document ingestion, chunking, and continuous pipelines • Working with Vector Databases (Azure AI Search, Qdrant, pgvector) • Running Cloud vs. Offline/Local LLMs using ONNX Runtime & Foundry Local • Monitoring latency and observability in .NET Aspire 🎯 Who This Video Is For: • C# / .NET Full Stack Developers • Software Architects & Technical Leads • Anyone looking to integrate Generative AI & RAG into .NET applications 📌 Resources & Links: • Semantic Kernel GitHub: https://github.com/microsoft/semantic... • Kernel Memory GitHub: https://github.com/microsoft/kernel-m... If you found this video helpful, don't forget to Like, Subscribe, and hit the Notification Bell for more C# and AI tutorials! 👍 #DotNet #CSharp #SemanticKernel #KernelMemory #AIEngineering #RAG #GenerativeAI #DotNet #CSharp #GenerativeAI #ArtificialIntelligence #SoftwareEngineering #SemanticKernel #KernelMemory #RAG #AIEngineering #VectorDatabase #AzureAISearch #DotNetDeveloper