Scalable AI Engineering Explained | Build AI Systems Like ChatGPT

Description

Modern AI applications are far more than simple chatbot demos. Behind every scalable AI platform are: distributed systems, async workflows, queues, vector databases, streaming infrastructure, caching systems, observability, and GPU-powered AI pipelines. In this video, we break down the real architecture behind scalable AI engineering and explore how modern AI systems like ChatGPT, GitHub Copilot, Perplexity, and enterprise AI platforms scale to millions of users. 🚀 In this video you’ll learn: ✅ High-level AI system architecture ✅ Async AI workflows ✅ Queues & worker systems ✅ RAG and vector databases ✅ Streaming AI responses ✅ AI caching strategies ✅ Rate limiting & cost optimization ✅ Monitoring & observability ✅ AI security & production infrastructure ✅ Real-world scalable AI engineering patterns This video is perfect for: Software Engineers Backend Developers AI Engineers System Design Preparation FAANG Interview Preparation Engineering Leaders Students learning modern AI infrastructure If you want to understand how real production AI systems work behind the scenes, this video is for you. 🔥 Don’t forget to Like, Share & Subscribe for more AI Engineering and System Design content. #AI #ArtificialIntelligence #SystemDesign #SoftwareEngineering #ChatGPT #RAG #LLM #BackendEngineering #AICoding #ScalableSystems #OpenAI #AIInfrastructure #DistributedSystems #Tech #Programming