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Praciller/README.md

Pakon Poomson

AI Engineer | GenAI Engineer | Data Engineer | RAG & Agentic Workflows

Portfolio Email LinkedIn

About

I am an AI Engineer at Seagate Technology focused on practical GenAI automation, internal engineering workflow tooling, and backend/data infrastructure. My current work includes multi-agent AI workflows for requirements analysis, debugging, testing, and PR preparation, plus C# internal software, VictoriaMetrics TSDB setup, and Kafka-to-TSDB ingestion validation with Apache Flink/Java.

Previously, I built full-stack applications and internal automation tools with React, Next.js, FastAPI, PostgreSQL, Directus, Supabase, and Docker. I focus on turning AI prototypes into usable software: reliable APIs, clean data flows, practical UX, and deployment-ready architecture.

Role Focus

Priority Target roles Evidence in this profile
1 AI Engineer RAG apps, LLM agents, multimodal extraction, AI automation, evaluation-minded delivery
2 GenAI Engineer / Data Engineer LangGraph, Qdrant, Gemini/Groq/Cerebras, pgvector, PostgreSQL, Kafka/Flink validation, VictoriaMetrics
3 Data Science / Data Analyst / Full-Stack / Frontend ML projects, analytics dashboards, React/Next.js, FastAPI, SQL, dashboards, API integrations

Core Stack

Area Tools and Strengths
AI / ML Python, TensorFlow, PyTorch, scikit-learn, LLMs, RAG, LangGraph, Qdrant, Gemini, Groq, Cerebras, Ollama
Data / Infrastructure Apache Kafka, Apache Flink, VictoriaMetrics, PostgreSQL, pgvector, Redis, SQL, time-series data, ingestion validation
Software Engineering TypeScript, Next.js, React, Node.js, FastAPI, C#, Java, Docker, CI/CD, Git/GitLab, REST APIs
Applied AI Agentic workflows, computer vision, OCR/entity extraction, multilingual summarization, document retrieval, structured AI outputs

Selected AI Credentials

  • AIAT Super AI Engineer Season 6: Foundation AI (Theory) - Artificial Intelligence Association of Thailand, 2026
  • Anthropic Academy certificates across Claude API, Claude Code, Model Context Protocol, subagents, agent skills, and AI Fluency
  • Google Cloud AI/ML skill badges across Vertex AI, Gemini, Imagen, Multimodal RAG, BigQuery ML, Document AI, and ML APIs
  • AIS Academy Prompt Engineering & Agentic AI

Featured AI Engineering Projects

Project What I built What it proves
Customer Support RAG Triage Agent (demo) LangGraph workflow for intent classification, urgency detection, Qdrant retrieval, grounded response generation, provider fallback, caching, and offline evaluation RAG architecture, agentic workflows, retrieval evaluation, FastAPI, React, Docker
Receipt AI Expense Tracker (demo) Local-first multimodal product that parses Thai/English receipts, validates structured output, normalizes Buddhist Era dates, and stores reviewed expenses in IndexedDB Multimodal AI, provider routing, Zod contracts, local-first design, Next.js analytics
AI Resume Matcher (demo) PDF-to-job analysis platform with strict validation, multi-provider routing, skill-gap guidance, interview preparation, deterministic mock mode, and Vercel deployment Production-minded AI APIs, Pydantic schemas, safe rendering, testing, React/FastAPI delivery

Data & ML Projects

Project What I built What it proves
Climate CO2 Forecasting ML Reproducible time-series pipeline comparing baseline, statistical, scikit-learn, and PyTorch models with shared evaluation and anomaly analysis Leakage-safe forecasting, chronological validation, model comparison, FastAPI, React
Explainable Cancer Diagnosis ML (frontend showcase) Breast-cancer classification benchmark with safety-relevant metrics, SHAP explanations, strict inference contracts, and an evidence dashboard Explainable ML, error analysis, model governance, scikit-learn, PyTorch, SHAP
Thai Procurement Intelligence (demo) Thai/English procurement search and analytics platform with ingestion, normalization, hybrid retrieval, dashboards, and evidence-backed Q&A Data engineering, public-data systems, PostgreSQL/pgvector, FastAPI, Next.js, LLM integration

Current Focus

  • Building GenAI workflow automation for requirements analysis, debugging, testing, and PR preparation.
  • Shipping RAG, multimodal AI, and agentic applications with production-minded APIs and data flows.
  • Strengthening backend/data infrastructure with time-series storage, Kafka/Flink validation, and PostgreSQL/pgvector.
  • Hardening AI applications with better evaluation, observability, testing, and deployment workflows.

Contact

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  1. customer-support-rag-triage-agent customer-support-rag-triage-agent Public

    Deterministic LangGraph support triage with Qdrant retrieval, grounded responses, evaluation, and an inspectable React console.

    Python

  2. receipt-ai-expense-tracker receipt-ai-expense-tracker Public

    Local-first multimodal receipt expense tracker with Gemini routing, Thai/English parsing, Zod validation, IndexedDB storage, and analytics.

    TypeScript 1 1

  3. ai-resume-matcher ai-resume-matcher Public

    Production AI resume matcher with FastAPI, React, validated multi-provider analysis, skill-gap guidance, and interview preparation.

    Python

  4. climate-co2-forecasting-ml climate-co2-forecasting-ml Public

    Atmospheric CO2 forecasting and anomaly detection with Python, PyTorch, FastAPI, React, Docker, and reproducible time-series evaluation.

    Python

  5. explainable-cancer-diagnosis-ml explainable-cancer-diagnosis-ml Public

    Explainable breast cancer classification with scikit-learn, PyTorch, SHAP, FastAPI, React, Docker, and CI.

    Python

  6. thai-procurement-intelligence thai-procurement-intelligence Public

    Bilingual Thai procurement intelligence platform with governed official-data ingestion, PostgreSQL/pgvector search, provenance, quality evidence, and cited AI assistance.

    Python