My journey into AI systems began with a foundation in software development and cloud computing architecture. After completing my MSc in Cloud Computing, I recognized that the next frontier in building scalable, intelligent platforms lay in operationalizing machine learning models and large language systems.
Today, I focus on designing and deploying production AI systems that solve real business problems. My work centers on LLM-based agents, document intelligence platforms, and automated workflows that leverage both pretrained and fine-tuned models. I prioritize system design thinking—ensuring that AI components integrate cleanly with existing infrastructure, handle scale, and maintain reliability.
Beyond implementation, I care deeply about architecture decisions: when to use pretrained models versus fine-tuning, how to structure agent-based systems for maintainability, and how to build AI platforms that are both secure and compliant with regulatory requirements.
Production code I've built remains private under organization accounts, as is standard for proprietary platforms. I share technical insights through architecture documentation, system design case studies, and technical decision records that focus on patterns and principles rather than implementation details.