Iβm a backend systems researcher and founder of Codetec Inc. β passionate about building scalable, intelligent, and fault-tolerant backend architectures.
My expertise spans microservice ecosystems, high-performance computing, and data-intensive systems using Python, FastAPI, GraphQL, and PostgreSQL.
Currently leading backend engineering at FlowRMS (U.S.), I focus on:
- βοΈ Distributed microservices on Kubernetes
- π§ Knowledge-driven AI integrations for enterprise platforms
- π Performance-optimized APIs for real-time analytics
When Iβm not engineering or researching, Iβm usually training early in the morning, mentoring developers, or exploring new intersections between AI and backend systems.
Panama | Nov 2022 β Present
Building robust RESTful API infrastructures that power businesses across Panama and beyond.
βAt Codetec, every endpoint is a promise of precision.β
Remote, U.S. | Dec 2023 β Present
- Architected distributed systems with FastAPI, GraphQL, and PostgreSQL.
- Engineered a knowledge library and AI bot for dynamic enterprise data interaction.
- Deployed scalable microservices on Kubernetes ensuring fault tolerance.
United States | Nov 2019 β Dec 2023
- Backend engineer for RIDSI and P3DB, high-impact research platforms.
- Designed CUDA kernels inside PostgreSQL for high-speed analytics on irregular time series.
- Published multiple IEEE papers on data-intensive computing and GPU acceleration.
- GPU-Accelerated PostgreSQL for Scalable Management and Processing of Irregular Time-Series Data β IEEE Big Data, 2023
- HTIDB: Hierarchical Time-Indexed Database for Efficient Storage and Access to Irregular Time-Series Health Sensor Data β IEEE EMBC, 2022
- Enabling Scalable Analytics of Physiological Sensor and Derived Feature Multi-Modal Time-Series β IEEE Big Data, 2022
π Master of Science, Computer Science β University of Missouri (GPA 3.88/4.0)
π Bachelor of Science, Computer Science β University of Missouri (GPA 3.98/4.0)


