Software Engineer · AI/ML Systems · Cloud & DevOps
A Master's graduate in Computer Science with strong experience in backend engineering, AI systems, and data platforms. I build scalable, high-performance systems for AI-driven applications.
Currently at Rackspace Technology, I design multimodal AI pipelines (OCR + LLM) for document processing and lead GraphQL API development for enterprise data platforms on Azure Cloud.
Previously at VNG Corporation, I built big data platform APIs, managed Kubernetes infrastructure, and developed React/Electron desktop applications for data engineering teams.
OCR, LLMs, Prompt Engineering, RAG Systems, GPT-4 Vision, Multimodal Pipelines
PostgreSQL, ClickHouse, MongoDB, Redis, Kafka, Azure Databricks, Cosmos DB
AWS, Azure, Docker, Kubernetes, Helm, Nginx, GitLab CI/CD, Linux
Node.js (Express/NestJS), Python (Flask/FastAPI), Golang (Gin), GraphQL, REST APIs
React.js, Electron.js, Redux, Umi.js, HTML/CSS, Ant Design, Responsive UI
Distributed Systems, Microservices, System Design, Event-Driven Architecture
Designed AI-powered document processing systems using OCR + LLM pipelines on Azure. Led GraphQL API development achieving 90% reduction in query times. Built automated deployment pipelines with Databricks Asset Bundles.
Developed RESTful APIs for big data platforms using Node.js, Python, and Golang. Managed Kubernetes applications with Helm. Built React.js and Electron.js interfaces. Implemented comprehensive E2E testing with Cypress and Mocha.
A micro-learning mobile app that teaches Mandarin Chinese through lock screen widgets and a TikTok-style word feed. Features AI-powered search, stroke order animations, native TTS pronunciation, and shareable word cards.
Master's thesis: Multimodal OCR–LLM pipeline for solar engineering drawings. 100% classification accuracy, >80% extraction accuracy.
I'm always open to discussing new opportunities, interesting projects, or just having a chat about tech.