I’m a Cloud & AI Consultant at Microsoft GCID with 8+ years of experience across software engineering, cloud-native architecture, enterprise modernization, and applied AI. My journey has evolved from Software Engineer to Associate Architect and now Cloud & AI Consultant, while remaining grounded in hands-on engineering. I believe strong architecture should stay connected to implementation, so I’m comfortable moving between business and architecture discussions, system design, technology decisions, and code-level problem solving. My engineering foundation spans C#/.NET, microservices, Azure PaaS, APIs, SQL, distributed systems, and cloud-native development, with an emphasis on building solutions that are secure, scalable, observable, resilient, maintainable, and cost-aware. Today, my focus extends into Generative AI, Retrieval-Augmented Generation (RAG), conversational AI, and agentic AI patterns, particularly how these capabilities can be integrated into real enterprise systems rather than remaining isolated experiments. Across my experience, I’ve worked with Azure OpenAI, Azure AI Search, semantic search, LLM-based intent identification and reranking, enterprise data retrieval, prompt-based orchestration, and AI-assisted workflows. Key areas of interest and expertise include: • Cloud & AI architecture and application modernization • RAG and agentic AI architecture patterns • Integration of LLMs with enterprise data, APIs, tools, and workflows • Building secure, scalable, and observable Azure cloud-native platforms • Responsible AI, security, governance, observability, reliability, and cost optimization • Bridging the gap between architecture and hands-on engineering What interests me most is the intersection of engineering, architecture, AI, and business: understanding the real problem, choosing the right technology, and turning ideas into solutions that can operate reliably in production. Think architecture. Understand the code. Solve the problem. Build for production. My goal is to help organizations move beyond AI experimentation and build responsible, production-ready Cloud & AI capabilities that create meaningful business value at scale.