Interactive

Jaehyeok Choi

AI Engineer

Seoul, South Korea wowogur12@naver.com github.com/choijhyeok linkedin.com/in/choijh0119

Profile

AI Engineer specializing in LLMs, RAG, Agentic AI, and large-scale document processing pipelines. Strong experience in designing and implementing end-to-end generative AI systems, from PoC development to real-world, production-oriented scenarios.

Work Experience

AI Engineer | KT Seoul, South Korea
Jul 2024 — Present
  • Delivered multiple enterprise-grade GenAI PoCs for legal, finance, media, and global clients
  • Designed complex Agent-based systems, including RAG, Web Search Agents, and Realtime Voice Agents
  • Built end-to-end solutions on Azure, from data processing to demo web deployment
Data Scientist | AIFactory Seoul, South Korea
Apr 2022 — May 2024
  • Designed and validated AI competitions and enterprise PoCs across LLM, CV, and time-series domains
  • Built LLM fine-tuning pipelines, RAG systems, and performance evaluation workflows (RAGAS)
  • Implemented large-scale data preprocessing and automated inference pipelines
Data Scientist | GSITM Seoul, South Korea
Jul 2021 — Jan 2022
  • Developed forecasting and optimization models for retail and logistics domains
  • Implemented demand forecasting and matching algorithms for real-world business operations

Key Projects (KT)

AI Engineer, Large-scale Insurance Policy RAG Pipeline (Meritz)

May 2025 — Dec 2025
  • Designed and implemented a large-scale RAG pipeline for 280,000 insurance policy documents
  • Built an end-to-end indexing workflow using Azure Durable Functions
  • Developed custom loaders for PDF, PPT, Excel, and JSON sources
  • Implemented table-stable extraction and custom chunking logic using PyMuPDF
  • Applied a Parent–Child RAG architecture on Azure AI Search

AI Engineer, AI Branch – Realtime Voice-based AI Banker (Shinhan Bank)

Jan 2025 — Apr 2025
  • Built a voice-to-voice AI banker PoC using the GPT-4o-Realtime API
  • Implemented WebSocket-based real-time streaming pipelines
  • Developed loan recommendation agents using Function Calling
  • Integrated Azure AI Search for financial product retrieval and reasoning
  • Deployed the full system on Azure Container Apps

AI Engineer, Web Search Agent (Giga Genie / JTS Thailand)

Sep 2024 — Mar 2025
  • Developed multiple Web Search Agent PoCs based on Bing Search
  • Designed agent workflows using LangGraph
  • Reduced hallucinations using Self-RAG and Corrective-RAG
  • Achieved up to 94% answer accuracy with sub-10s response latency
  • Built demo applications using Gradio

AI Engineer, Legal RAG System PoC (Korea Forest Service)

Aug 2024 — Dec 2024
  • Built a legal-domain RAG system PoC for statutes and legal precedents
  • Designed a combined LLM fine-tuning + RAG architecture
  • Achieved Top-5 retrieval accuracy of 93.51%
  • Evaluated performance with RAGAS (Context Precision, Recall, Faithfulness > 90)
  • Developed a demo web using Gradio and pdf.js with source highlighting

Selected Projects (AIFactory)

Data Scientist, LLM Fine-tuning and RAG Evaluation

  • Fine-tuned LLaMA2, Gemma, and EEVE models using QLoRA and DeepSpeed
  • Built RAG pipelines and evaluated performance using RAGAS
  • Developed crawling pipelines for external data collection

Data Scientist, AI Competition Design (CV / Time-Series)

  • Designed challenges for Object Detection, Segmentation, and Pose Estimation
  • Built datasets in COCO format and defined evaluation metrics (Macro F1, IoU, MAE)
  • Led competition design and validation for multiple enterprise and public clients

Selected Projects (GSITM)

Data Scientist, Retail Sales Forecasting System

  • Preprocessed convenience store sales data with seasonality analysis
  • Built Prophet-based sales forecasting models
  • Proposed inventory optimization strategies based on forecast results

Data Scientist, Genetic Algorithm-based Logistics Matching

  • Implemented optimization algorithms using DEAP
  • Developed matching logic to maximize profit under weight and cost constraints
  • Improved logistics efficiency and operational decision-making

Personal Projects & Talks

Open Source Maintainer, Korean HWP/HWPX Document Parsing Open Source

  • Developed Python libraries for parsing HWP and HWPX documents
  • Addressed real-world limitations of Korean document processing in Python environments
  • Resources: GitHub Repo, LinkedIn Post

Personal Project, Gemma Function Calling Assistant

  • Fine-tuned Gemma 7B using SFT to enable Function Calling
  • Built a personal assistant that executes external tools and delivers results via KakaoTalk

Speaker / Open Source Contributor, LLaMA2 Fine-tuning & RAG Pipeline

  • Presented an end-to-end LLaMA2 fine-tuning and RAG pipeline
  • Implemented QLoRA-based instruction fine-tuning optimized for Colab T4
  • Built an easy-to-use fine-tuning pipeline with a Gradio UI
  • Resources: GitHub Repo, YouTube Talk

Speaker, Building RAG-based Services with Streamlit & LangChain

  • Speaker at LangChain KR Meetup (2024 Q1)
  • Demonstrated deployment of RAG-based AI services using Streamlit
  • Explained vector DB separation and QA-chain-based recommendation architectures
  • Showcased automated report generation pipelines (HTML → PDF)

Education

Gyeongsang National University

B.S. in Information Statistics and Computer Science

Mar 2016 — Feb 2022

South Korea

Skills

Languages
Python JavaScript SQL
LLM / GenAI
RAG LangChain LangGraph Fine-tuning Function Calling RAGAS
Infrastructure
Azure Functions Azure AI Search Azure Container Apps Docker
Document Processing
PyMuPDF OCR Large-scale Document Pipelines