{
"name": "Surakiat Kongchana",
"alias": "BBEER",
"title": "AI Engineer",
"location": "Bangkok, Thailand",
"education": "B.Sc. Data Science & Analysis @ Naresuan University",
"experience": [
"AI Engineer @ Supalai PCL (Current)",
"AI Engineer @ CP Axtra (Lotus's)",
"AI Engineer @ AIAT (Super AI S5)",
"Back-End Developer @ Enov8 (Sydney)"
],
"skills": [
"RAG, LangGraph, LangSmith, MCP, Multi-Agent",
"Azure OpenAI, OpenAI API, Prompt Engineering",
"FastAPI, Python, Docker, BentoML",
"PostgreSQL, Qdrant, Elasticsearch, Microsoft Fabric"
],
"governance": "OpenMetadata, RBAC, Text-to-SQL, SQLGlot, PII",
"achievements": "Super AI Engineer S5, depa GrowthLab Finalist, Beyond Coding Finalist",
"status": "🎯 Building agentic AI"
}
สวัสดีครับ! ผมเป็น AI Engineer ที่มีประสบการณ์ในการพัฒนา RAG Chatbot, Agentic AI และ Backend Systems ปัจจุบันเป็น AI Engineer ที่ Supalai (Bangkok) ทำงานด้าน Agentic Data Governance, Text-to-SQL และ AI Call Center เคยทำงานที่ CP Axtra, AIAT และ Enov8 (Australia) และกำลังศึกษาอยู่ที่มหาวิทยาลัยนเรศวร 🚀
Building Minicooper, an Azure OpenAI-powered agentic data governance copilot for natural-language analytics over enterprise business datasets: secure text-to-SQL with SQLGlot validation, OpenMetadata RBAC, semantic search and PostgreSQL logging, hardened with deterministic evals, adversarial security tests and Locust load testing. Also built a Thai AI call-center sales assistant that transcribes calls, labels speakers, redacts PII, extracts insights, scores leads and produces CRM-ready outputs, with React/Streamlit dashboards and a Dockerized deployment.
Architected and deployed LotusAI, a 4-stage AI ecosystem (Support Chatbot, Customer Chatbot, Token Control, GitLab AI Helper) using RAG, LangGraph, Qdrant, Redis and FastAPI. Built containerized Python microservices for scalable vector search and added short-term memory to the RAG pipelines, with Chainlit UIs and LangSmith for prompt optimization. Achieved 60% token reduction, 40% latency improvement and 70% cost savings, improving support resolution from 10min to 1-2min with CSAT 4.4/5.
Collaborated with cross-functional teams to prototype and deploy end-to-end AI services: built FastAPI inference endpoints, integrated large language models (LLMs) and generated synthetic datasets using REaLTabFormer & SDV. Completed five domain-specific hackathons plus a 24-hour grand finale as part of the Super AI Engineer Program (Session 5) and reached the finals in the Demo Day AI ChatBot competition.
Conducted R&D on REaLTabFormer papers for synthetic data generation with REaLTabFormer, Faker and SDV. Worked as a Back-end Developer using Python and FastAPI to support international teams, and experimented with LLM and Ollama for synthetic data generation.
Azure OpenAI-powered data copilot for governed natural-language analytics over enterprise datasets. Secure text-to-SQL with SQLGlot validation, OpenMetadata RBAC, semantic search, PostgreSQL logging and dashboard monitoring. Added deterministic evals, adversarial security tests and Locust load testing.
Thai AI call-center assistant that transcribes sales calls, labels speakers, redacts PII, extracts insights, scores leads and generates CRM-ready outputs. Built the backend API, Azure OpenAI analysis pipeline, lead-scoring model, React/Streamlit dashboards and a Dockerized deployment.
Support Chatbot, Customer Chatbot, Token Control and a GitLab AI Helper built on RAG with short-term memory. Containerized Python microservices for vector search, Chainlit UIs and LangSmith prompt optimization. 60% token reduction, 40% latency improvement, 70% cost savings, CSAT 4.4/5.
AI code search & deployment tracking with <1% error rate. Improved developer workflow and code quality at CP Axtra.
AI-powered Line chatbot serving 1,000+ event attendees. Automated FAQs, schedules, awards, venue navigation. Reduced staff workload.
FastAPI inference endpoints, LLMs integration, synthetic datasets using REaLTabFormer & SDV at AIAT.
AWS-powered GenAI Hackathon in Chiang Mai. Finalist in Demo Day round (AI ChatBot).
Data Science and Machine Learning competition. Finalist and award recipient. Collaborated with Botnoi.
R&D on REaLTabFormer papers at Enov8 (Sydney). Synthetic data generation using REaLTabFormer, Faker, SDV. LLM & Ollama experimentation.
5 domain-specific hackathons + 24-hour grand finale. NLP, Computer Vision, Data Science, IoT, Signal Processing.
Intensive AI-engineering curriculum covering system architecture, data pipelines, production deployment, NLP, computer vision, data science, IoT, and signal processing. Completed 5 domain-specific hackathons + 24-hour grand finale.
Built an AI-powered Line chatbot serving 1,000+ event attendees with real-time information. Automated FAQs about competitions, schedules, awards, and venue navigation. Reduced staff workload through instant, reliable responses.
Participated in Hackathon training program in Chiang Mai. Finalist in the Demo Day round (AI ChatBot).
Participated in Beyond Coding competition for Data Science and Machine Learning. Finalist and award recipient. Collaborated with Botnoi on related projects.
Bachelor of Science Program in Data Science and Analysis. Phitsanulok, Thailand.
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