Chirawat Chitpakdee

"Tech Lead Engineer | AI, RPA & Automation Workflow Specialist
Driving Digital Transformation Through Intelligent Automation"

Versatile automation engineer specializing in end-to-end business process transformation through cutting-edge technologies including Python, low-code platforms, and Agentic AI. Expert in designing and implementing intelligent automation solutions that streamline operations—from automated data reconciliation and real-time analytics to AI-powered chatbots (RAG) and API services. Proven track record in delivering measurable results through performance optimization, cost reduction, and scalable automation frameworks that transform routine processes into strategic advantages.

Key Responsibilities:

• Lead design and implementation of automation solutions for business process optimization
• Architect and develop RPA workflows and intelligent automation systems
• Build and deploy AI-powered applications including RAG-based chatbots with MCP integration
• Design, deploy, and maintain enterprise AI API services and AI server infrastructure
• Provide expert consultation for AI application development and LLM-based data cleansing solutions
• Setup automation infrastructure: Power Automate machines, Linux servers with Cronicle scheduler, AI servers
• Drive digital transformation initiatives across multiple business units
• Mentor junior engineers and establish best practices for automation development

Key Responsibilities:

• Promoted digital economy initiatives and supported SMEs in adopting digital technologies
• Developed and delivered digital skills training programs for workforce development
• Drove smart city initiatives through technology and innovation solutions
• Supported digital startup ecosystem through mentorship and resource provision
• Organized workshops, seminars, and provided technology consulting

Key Responsibilities:

• Conducted computational chemistry research using DFT and ML for materials design
• Investigated photophysical properties of organic materials for renewable energy applications
• Developed theoretical models for catalytic systems and CO2 electrochemical reduction
• Presented research findings at international conferences and delivered computational chemistry lectures

Key Achievements:

• Published 17+ peer-reviewed articles with 335+ citations (h-index: 11)
• Developed ML-based predictive models for catalyst performance and material property screening
• Presented at 10+ international conferences including EMRS2019 (Nice, France), WATOC2017 (Munich, Germany)
• Served as VASP computational software lecturer at Summer School workshops