Backend & Applied AI Engineer
Product-minded backend engineer with production and research experience across APIs, event-driven systems, robotics, simulation, data pipelines, and applied AI. Strongest in Python backend development, with end-to-end range across TypeScript interfaces, cloud delivery, observability, and operational workflows.
Backend: Python, FastAPI, Flask, Node.js, REST APIs, PostgreSQL, MongoDB, Redis, SQL
Applied AI & data: LLM systems, RAG, contextual bandits, PyTorch, scikit-learn, Pandas, MLflow, simulation
Delivery: AWS, Docker, CI/CD, Linux, observability, React, Next.js, TypeScript
Public synthetic-data ingestion reference with OIDC/JWT authorization, async validation, idempotent persistence, retries, dead-letter handling, observability, tests, and CI.
Live Belize property discovery and operations platform with real inventory, buyer qualification, CRM workflows, parcel geometry, provenance boundaries, and consent-aware measurement.
Digitized tour-operator workflows with an approximately 40% reduction in reported accounting errors; separately analyzed 10,078 railway failures across 279 stations.
Master of Engineering, IT & Energy Convergence · Korea National University of Transportation · 2024–2026
Bachelor of Science, Information Technology — Magna Cum Laude · University of Belize · 2018–2022
AWS Certified Solutions Architect – Associate · Amazon Web Services