Designed and implemented a Kubernetes operator using Go to autonomously provision and integrate user data pipelines into the monitoring system. Resulted in streamlined operations and saving multiple operational hours per pipeline

Designed and executed an experiment to evaluate and contrast different load generator alternatives, resulting in data-driven recommendations for an optimal-performanced one

Revamped CI/CD pipeline through GitHub Actions, streamlining workflows with Makefile scripting. Significantly reduced integration and deployment times by more than 3x

Played a pivotal and leading role in the Engineering organization to secure Series A funding for the company. Funding round led to a 5x increase in company valuation by raising more than 10 million USD

Architected and implemented a backend service leveraging Python 3.9, Django 3.4, and PostgreSQL 12 to gather and analyze U.S. real estate property data, successfully processing 10k+ raw data entries weekly

Designed and scaled an internal tooling service that allows employees to enhance their work efficiency (e.g., construction, managing internal information).

Led efforts in forecasting investment viability with 85% precision via TensorFlow and Pandas

Orchestrated a seamless CI/CD framework using Terraform, AWS ECS, AWS Fargate, and GitHub Actions, streamlining deployment procedures and ensuring code integrity, which significantly reduced deployment time and overhead

Designed and developed core web application with ReactJS and Firebase

Selected as a startup to represent early-stage software companies in IF2019; the largest startup festival in South Korea.