Seoul, South Korea
I started programming as a hobby in elementary school, building small tools out of curiosity. That early interest naturally evolved into a career. Today, I’m a software engineer focused on building scalable backend systems for AI-powered products, currently working at TwelveLabs to serve multimodal AI models (Marengo, Pegasus) in production. My work centers on designing and operating backend systems that enable reliable, low-latency access to video understanding AI. I focus on user-facing APIs, video data processing pipelines, indexing systems, and communication layers between ML services and production systems. Previously, I led engineering teams at a fast-growing startup (0 → Series B), where I: - Built and scaled a microservices-based logistics platform serving 100k+ devices - Designed real-time IoT data pipelines and event-driven architectures - Led system architecture, hiring, and engineering processes While I have leadership experience, I currently focus on being a hands-on engineer, working deeply on backend systems, scalability, and production reliability. I’m particularly interested in: - Distributed systems & event-driven architecture - Large-scale video and AI-powered applications - ML service integration at scale
- Built and maintained backend systems to serve multimodal AI models (Marengo, Pegasus) and embedding APIs (Embed-v2) in production - Designed and served core APIs (search, analyze, embed) enabling scalable access to video understanding capabilities - Built the first user-facing SDKs (Python, Node.js) and improved developer experience and accessibility - Led the transition from manual SDKs to auto-generated SDKs using Fern based on API specifications - Revamped video indexing and developed Entity Search and Assets APIs for efficient querying and management of large-scale video data - Built core platform services including IAM, Notification Service, and enterprise on-premise deployments - Implemented GDPR-related features to support data privacy and compliance requirements - Designed backend systems that bridge ML services with user-facing APIs, ensuring reliable and low-latency AI serving
- Developed and maintained backend systems for an RFQ (Request for Quotation) platform - Designed APIs and optimized database queries for service performance and scalability - Improved operational workflows for service provider management
- Led a cross-functional engineering team (BE 3 / FE 3 / Mobile 2 / Design 1 / PM 2), scaling from 0 → Series B stage - Architected and delivered a microservices-based logistics platform serving 100k+ devices, improving scalability and system reliability - Built real-time IoT data pipelines processing millions of events per day for device monitoring and analytics - Designed and implemented event-driven systems for logistics tracking and device telemetry - Led development of internal systems: - Back-office & customer support platform - Device(BLE/LTE/QR/NFC) monitoring services - Logistics operation and dispatch applications - Owned AWS infrastructure and cost optimization, improving operational efficiency - Established CI/CD pipelines and engineering best practices - Led legacy system migration from Spring Boot / ASP.NET to NestJS + React - Built and scaled the engineering hiring process
- Led development and delivery of multiple outsourced software projects - Designed and implemented mid-to-large scale applications (frontend to backend) - Key projects: - University enrollment system for Chungcheong education offices - ML server management system (reservation / remote control / monitoring) - Facility maintenance application (research project with Hongik University) - Conducted performance analysis and system optimization
- Started software development at an early age, building websites and systems for small businesses and schools - Developed outsourced websites and attendance management systems for academies