Pink Web Portfolio

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About Me

My name is Isariya Sirivejabandhu, but you can call me Pink. I am a Software Engineer with 4+ years of experience in web development and system support, with practical experience in cloud infrastructure, DevOps workflows, and containerized environments. Experienced in collaborating with cross-functional teams to support scalable and reliable systems, and motivated to grow into a Cloud or Platform Engineering role

My Education

Kasetsart University, Thailand

2014 - 2018

Bachelor of Science in Computer Science

National Central University, Taiwan

2021 - 2023 | GPA 4.00

Master of Computer Science and Information Engineering

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Work Experience

Software Engineer — Ticketmaster

Jun 2024 – Dec 2025

Developed and maintained frontend and backend features for Ticketmaster platforms across Southeast Asia, including Singapore, Thailand, and the Philippines, using PHP (Yii Framework), JavaScript, HTML, CSS, Bootstrap, SQL, and AWS.
Improved engineering team productivity by leading tool transitions from Redmine → Asana → Jira, including board setup, workflow rules, automations, Agile processes, and Confluence documentation.
Designed and implemented Slack bot integrations for Jira using Node.js, AWS Lambda, API Gateway, with automated deployments via GitLab CI/CD and Terraform.
Migrated infrastructure to Amazon EKS Auto Mode, managed internal services (e.g., Gitea) using Argo CD, and deployed Helm-based applications following GitOps best practices.

Software Engineer — RS Public Company Limited

Sep 2020 – Dec 2021

Built and maintained WordPress websites with custom themes and basic SEO optimization.
Resolved production issues to ensure system stability and on-time delivery.
Collaborated with designers and developers to deliver user-friendly, high-quality websites.

Software Engineer — Pronto Marketing

May 2019 – Aug 2020

Developed responsive WordPress websites using HTML, CSS, JavaScript, and PHP.
Collaborated with cross-functional teams in an Agile environment to deliver high-quality web solutions.
Provided technical support and mentored new hires on web technologies and best practices.

More About My

Skill

Software & Web Development

javascript

Python

React.js

Node.js

Wordpress

PHP

Yii

HTML

CSS

Bootstrap

NoSQL

SQL

LESS

sass/scss

jquery

AI & Machine Learning

Tensorflow

Pytorch

Deep learning

Cloud & DevOps

Kubernetes

AWS

Docker

Terraform

Helm

ArgoCD

GIT

Dive Into My

Certifications

AWS Certified Solutions Architect – Associate

Issued By: Amazon Web Services

Focus Areas: Cloud Architecture, High Availability, Security, VPC Design, Scalable Deployments, Cost Optimization

Designed and deployed scalable, fault-tolerant AWS architectures. Hands-on with EC2, S3, IAM, RDS, VPC, CloudFront, and CloudWatch, with strong emphasis on security and cost efficiency.

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Certified Kubernetes Administrator (CKA)

Issued By: The Linux Foundation (CNCF)

Focus Areas: Cluster Architecture, Workloads & Scheduling, Networking, Storage, Troubleshooting

Managed production-grade Kubernetes clusters. Configured workloads, ingress, services, and persistent storage. Developed strong troubleshooting skills across cluster, node, and application layers.

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Take a look at My

Thesis

Thesis Topic: A Graph-base Approach for PM2.5 Prediction

Supervisor: Professor Min-Te Sun

Mainly About: Spatio-Temporal Problem, Timeseries Forecasting, Graph-based model, PM2.5 Prediction, Deep Learning

Project Detail:

We proposed a PM2.5 prediction system that includes data preprocessing, data fusion, feature engineering, feature selection, and the proposed prediction model, DCRNN-GS. The DCRNN-GS model combines the strengths of DCRNN, which has the ability to capture spatio-temporal dependencies in sequential data, and GraphSAGE, which is capable of learning meaningful information for each node in the graph. We achieved a significant 5.66% MSE improvement compared to state-of-the-art approaches, highlighting its superior performance in forecasting for iterative multistep prediction for the next 24 hours based on the past 24 hours of data.

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Publication

Title: A Graph-based System for PM2.5 Prediction

Published In: I-SPAN Ubi-Media 2025, Springer CCIS Vol. 2380, Singapore

Overview:

Proposed an end-to-end PM2.5 forecasting system using graph-based learning, integrating spatio-temporal features, data preprocessing, and a hybrid DCRNN–GraphSAGE model (DCRNN-GS). Demonstrated improved prediction performance for iterative multistep forecasting across 24-hour horizons.

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Explore My

Cloud Projects

Real-world cloud architectures designed and built with AWS services, following serverless best practices, infrastructure-as-code, and production-ready patterns.

Serverless Todo List API

End-to-end serverless application using AWS Lambda, API Gateway, DynamoDB, S3, CloudFront, and GitHub Actions for CI/CD. Built with fully automated IaC using Terraform.

AWS Lambda API Gateway DynamoDB S3 Bootstrap HTML Terraform GitHub Actions Node.js CSS