Back in my early engineering days at Daikin HVAC, I spent countless hours diagnosing industrial refrigeration systems, tuning physical feedback controllers, and managing sensor data pipelines. Working with physical thermodynamics taught me the unyielding truth of production systems: failure modes will always occur at the boundaries, and real-time reliability is non-negotiable.

That passion for robust, deterministic architectures naturally led me to pivot into distributed backend engineering and cloud infrastructure. Today, I architect and build async, event-driven microservices using Node.js, Go, Python, and PostgreSQL, specializing in resilient financial platforms and high-throughput enterprise systems.

My primary technical focus is bridging modern AI systems with production backends: integrating large language models (LLMs), LangGraph/LangChain agentic workflows, and semantic retrieval into scalable architectures. I care deeply about token telemetry, deterministic fallbacks, and building software that consistently delivers value at scale.