I build production-ready AI applications, focusing on making LLMs truly functional for complex, enterprise-scale tasks. My work bridges the gap between experimental AI and dependable software architectures.

• 🤖 Agentic AI: Designing and delivering end-to-end architectures and autonomous agent workflows.
• 🏗️ Orchestration: Building reusable frameworks and advanced prompt orchestration patterns.
• 🔍 RAG Pipelines: Developing and optimizing high-performance Retrieval-Augmented Generation systems and vector database indexing.
• ☁️ Enterprise Delivery: Deploying scalable Generative AI solutions within cloud and containerized environments.

• Specialized Areas: AI Agents, Agentic Workflows, RAG, LLM Orchestration, Prompt Engineering.
• Deep Learning: Transformers, LLMs, NLP, Sequence-to-Sequence models.

• Languages & Data: Python (Pandas, NumPy), SQL.
• ML & NLP Tools: Scikit-learn, NLTK.
• Visualization: Matplotlib, Seaborn.
• Infrastructure: Azure, Docker, Git/GitHub, SQL Server.

I'm always looking to exchange ideas with others building in the GenAI and Cloud space. Whether you're wrestling with agentic loops or optimizing retrieval, feel free to reach out!

• 💬 Ask me about: RAG optimization, Agentic patterns, or productionizing LLMs.