PIYAPONG MUNGTHONG

A motivated ICT graduate with a solid foundation in Software Development and Infrastructure. Hands-on experience building web services using Go, Python, and Node.js, combined with practical knowledge of Docker, Kubernetes, and AWS. Eager to contribute to a collaborative engineering team, apply secure coding practices, and continuously learn to deliver efficient technology solutions.

• 2025 NCSA: Thailand Cyber Top Talent 2025
• 2024 Cisco academy: IoT Fundamentals: Connecting Things
• 2024 AWS academy: AWS Academy Cloud Developing
• 2023 Cisco academy: CCNAv7 Introduction to Networks Cisco Network Academy

2025 – 2026 Senior Project: Virtual Career Engagement Platform (VCEP), 

- Designed and managed Backend services with Go for database connectivity and optimized AWS server deployment., 

- A platform designed to bridge the gap between students and industries through interactive virtual networking and data-driven engagement tools., 

- Defined scope and core feature directions through in-depth problem analysis and stakeholder requirement gathering., 

- Developed a comprehensive technical overview and conducted functional decomposition to translate requirements into structured module plans and system workflows., 

2025 Discord Member Management Bot | Python (discord.py), 

- Collaborated with community stakeholders to collect and analyze specific functional requirements for automated server management., 

- Developed an automated management system for community, featuring registration and user verification., 

- Implemented an Invite Tracker to monitor member sources and enhance server-side auditing., 

2024 DevOps Workshop: Kubernetes Networking, 

- Designed and managed application workloads by deploying Kubernetes Deployments and exposure layers., 

- Provisioned and integrated Cluster IP, Node Port, and Load Balancer services to handle distinct traffic routing scenarios., 

- Validated end-to-end network paths and performed load-handling tests to ensure high availability and proper service exposure to external networks., 

2024 AI-Powered Activity Monitoring System (IoT & TinyML), 

- Architected an end-to-end IoT ecosystem using M5Stack and ESP32, integrating TinyML for real-time human activity recognition via Edge Impulse., 

- Developed a Neural Network model to classify physical postures (e.g., arm-swing Vs. stationary) and deployed it as an edge computing service., 

- Developed a communication layer using MQTT protocol and Node-RED, enabling Dynamic system configuration and real-time data synchronization.