I am a Software Engineer and AWS Solutions Architect driven by the challenge of translating complex, manual business workflows into automated solutions that are both intuitive and high-value. With a B.S. in IT from George Mason University specializing in Database Technologies and Programming, my approach to full-stack development is rooted in the conviction that software must be reliable and easy-to-use. Whether I’m architecting cloud-native systems within the AWS ecosystem or engineering context-aware AI agents, my objective remains constant: building automated and intelligent tools that solve real-world frictions. I am particularly passionate about the intersection of Cloud Architecture and Generative AI, where I leverage AI and RAG-based systems to bridge the gap between raw data and human decision-making. To me, success is defined by delivering resilient, secure, and functional systems that scale effortlessly while providing a seamless, meaningful experience for the end user.
A cloud-native SaaS platform designed to transform fragmented financial data into actionable intelligence. This system ingests and normalizes disparate bank statements into a unified schema, enabling high-precision spending tracking and budget forecasting. The platform integrates AWS Comprehend for automated transaction categorization and AWS Bedrock, Langchain, & RAG to generate natural-language financial summaries, including spending pattern analysis and explanations of budget variances, shifting the user experience from manual data entry to automated financial advisory.
Key Tech: Java (Spring Boot), Python, AWS Serverless (Lambda, Step Functions, ECS, DynamoDB, Cognito), PostgreSQL, AWS Comprehend, AWS Bedrock (AI/ML), LangChain, AWS CDK (IaC), Microservices Architecture.
Financial Intelligence & AI-Driven Insights! [github]An compliance automation engine engineered to replace manual, error-prone data reconciliation workflows. The portal centralizes siloed data from HR, IT, Security, and Finance, performing domain-driven validation to detect compliance violations in real-time. By automating the "source of truth" verification process, the application significantly reduces manual oversight, detect violations early, and improves the auditability of internal records.
Key Tech: Python, Angular, PostgreSQL, Docker, AWS App Runner, Hexagonal Architecture for Domain-Driven Design (DDD).
Eliminating "Excel Engineering" through Automation! [github]A logistics and inventory management application developed for the Vietstar Shipping company. This application is used by the shipping company's employees to digitalize shipping procedures, and streamline inventory management process for their customers. I led a team of 5 to develop shipping and inventory systems for the logistics company. The project was initially built as a Capstone project, then modernized with production-grade cloud infrastructure and DevOps practices to reduce environment provisions and to improve system reliability, scalability, and high availability.
Key Tech: PHP, MySQL, AWS (EC2, ASG, RDS Multi-AZ, ALB), Terraform (IaC), GitHub Actions (CI/CD).
Modernizing legacy logistics through digital automation and scalable cloud infrastructure to streamline operations! [github]Engineered a conversational agent designed to handle customer inquiries with high precision. By leveraging LangChain and RAG (Retrieval-Augmented Generation), the chatbot moves beyond generic responses, utilizing prompt chainings, embeddings, and a vector-based knowledge base to provide contextually accurate answers rooted in company-specific data. This architecture minimizes LLM hallucinations and boost response accuracy.
Key Tech: LangChain, OpenAI, Python, FastAPI, RAG Architecture.
Generative AI & Knowledge Automation![github]A document intelligence platform capable of processing both native and scanned PDFs to extract concise summaries. The application bridges the gap between manual document review and automated data synthesis, utilizing OCR (Optical Character Recognition) to normalize scanned content before passing it through an NLP pipeline. Architected for scalability, the system ensures that high-volume document ingestion remains cost-efficient and performant.
Key Tech: Python, Pydantic, AWS Textract (OCR), AWS Bedrock, Langchain, Chroma vector store, MongoDB
Turning Unstructured Data into Actionable Insights![github]An environmental website that promotes environment-friendly activities.
My first website project![github]