About Me

I am a Systems Engineer and Full-Stack Architect with a First-Class degree in Engineering and over 5 years of experience. I specialize in building high-performance interfaces and AI systems that bridge the gap between heavy math and seamless user experience. I focus on turning technical bottlenecks into quick wins, like when I supervised a 60x speed optimization for Airflow and Kafka including orchestrating high-availability AWS deployments while prioritizing reliability and efficiency.

My work in AI is centered on practical, scalable solutions, including production-ready RAG systems and autonomous multi-agent dispatch engines like Locus, which coordinates seven specialized agents for real-time analysis. I have a deep interest in modeling complex systems, such as my Copernican simulator, which uses Kepler’s Laws and live NASA data to track planetary mechanics and environmental hazards. My experience ranges from building fleet logistics engines that predict hardware failure using Fluid Mechanics to developing modular UI component libraries that ensure long-term maintainability.

Beyond the technical stack, I am a high-agency collaborator who has doubled team efficiency and maintained 99.9% service reliability. I manage polyglot database environments spanning Postgres, Neo4j, and Vector databases with a focus on cost-effective cloud scaling. I am committed to building solutions that are fast, reliable, and fundamentally useful.