146 lines
7.6 KiB
YAML
146 lines
7.6 KiB
YAML
cv:
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name: "Ding-Lian Chen (陳定廉)"
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headline: "AI 後端工程師|RAG · Text-to-SQL · 微服務交付"
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location: "中和, 新北"
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email: "shadow449515@gmail.com"
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phone: "(+886) 0979508405"
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social_networks:
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- network: LinkedIn
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username: 定廉-陳-a4536036b
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- network: GitHub
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username: Dingian
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sections:
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summary:
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- "兼具後端研發與測試能力的工程師,能運用 Azure OpenAI 與 LangChain 獨立完成企業級 RAG 與 Text-to-SQL 微服務從 POC 到可部署原型的完整交付,亦具備 API 自動化測試與 Kubernetes 環境問題排查的實戰經驗,能快速融入不同技術棧的專案。"
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- "主導 Semantic Caching 優化將 LLM API 延遲由 ~3200ms 降至 ~30ms(50 CCU 壓測驗證);熟悉 FastAPI、Pydantic v2 與 SQLAlchemy v2 (Async) 非同步架構,以 RLS 多租戶隔離與 AST 解析 SQL Guard 確保高併發下的安全性與效能。"
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education:
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- institution: "National Taipei University (國立臺北大學)"
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degree: "Bachelor of Science"
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area: "Communication Engineering (通訊工程學系)"
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location: "New Taipei, Taiwan"
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start_date: "2021-09"
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end_date: "2025-06"
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highlights:
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- "相關修課:資料結構與演算法、數位訊號處理、資訊理論、計算機網路、線性代數、機率與統計。"
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- institution: "經濟部產業發展署 (IDA, MOEA) & 國立臺北大學"
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degree: "Professional Development"
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area: "AI 應用人才培育計畫 (智慧製造專班)"
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location: "New Taipei, Taiwan"
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start_date: "2025-08"
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end_date: "2025-11"
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experience:
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- company: "Galaxy Software Services (叡揚資訊)"
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position: "AI Backend Engineer Intern"
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location: "Taipei, Taiwan"
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start_date: "2025-12"
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end_date: "2026-03"
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summary: 參與多個產品線開發與品質驗證工作,涵蓋 AI 後端微服務核心開發、NPO 多租戶系統 E2E 自動化測試,以及 VDU 影像識別產品的資料標記作業 (Label Studio)。
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highlights:
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- "進階 Text-to-SQL:設計自然語言至母產品 JSON Schema 的動態映射層,運用 Few-shot Prompting 提升複雜業務邏輯下的 SQL 生成準確率。"
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- "RAG 與效能優化:設計 Semantic Caching 機制並導入 Redis 快取層,在 50 CCU 壓力測試下將 LLM API 延遲由 ~3200ms 降至 ~30ms,驗證低延遲架構可行性。"
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- "資安與數據治理:實作基於 AST 解析的 SQL Guard 防護機制,100% 攔截惡意 DDL/DML 操作;結合 PostgreSQL RLS 確保多租戶環境下的資料絕對隔離。"
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- "基礎設施與移交:建立 Shadow Wallet 機制進行 API Rate Limiting 防護;全案採用 uv 進行依賴鎖定,並撰寫 Podman Dockerfile,將開發至壓測環境的部署流程標準化以利團隊交接。"
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- "ETL 資料同步:設計並執行慈濟外部表單資料的全量與增量 Upsert 同步機制,確保本地資料庫與上游系統資料一致性。"
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projects:
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- name: "企業級 LLM Gateway 智能查詢微服務 (llm-bridge)"
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start_date: "2025-12"
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end_date: "2026-03"
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tech_stack: Python, FastAPI, Pydantic v2, SQLAlchemy v2, PostgreSQL, Redis, LangChain, Azure OpenAI, sqlglot, Podman, uv
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description: 以模組化單體 (Modular Monolith) 架構,為 NPO 多租戶 CRM 系統建構無狀態雲原生 AI 服務,讓 VIP 客戶以自然語言跨表單檢索業務數據。
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highlights:
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- "四模式智慧路由:透過 LLM 結構化輸出將使用者意圖強制分類為 FILTER / AGGREGATION / RANKING / ANOMALY_DETECTION,並搭配動態規則引擎進行熱更新業務邏輯注入,杜絕 LLM 幻覺。"
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- "AST 級防護與語意快取:以 sqlglot 進行 SQL 抽象語法樹深度解析,100% 阻斷 DML/DDL;結合 PostgreSQL RLS 強制注入 territory 邊界實現多租戶資料隔離;pgvector HNSW 向量索引支援語意快取,在 50 CCU 壓測下將 LLM 延遲由 ~3200ms 降至 ~30ms。"
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- "成本治理與 WAF:Shadow Wallet 整數運算防溢位模型精準計算 Token 成本並以 HTTP 402 攔截超額請求;Redis 分散式鎖 (SingleFlight) 防範快取擊穿;L7 動態黑名單限流器毫秒內阻斷高頻惡意請求。"
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- name: "慈濟微服務 E2E 自動化測試"
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start_date: "2025-12"
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end_date: "2026-03"
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tech_stack: Postman、Kubernetes (K8s)、k9s
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description: 針對 NPO 多租戶微服務系統設計並執行端到端 API 自動化測試,確保服務品質與上線穩定性。
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highlights:
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- "撰寫涵蓋正常流程、邊界條件與異常情境的 API 測試用例,使用 Postman 進行自動化測試與回歸驗證。"
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- "透過 k9s 或 kubectl 即時查看 Kubernetes 叢集服務日誌,定位並協助修復跨服務整合問題。"
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- name: "食道語者語音輔助裝置 (AI 聲學特徵分類系統)"
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start_date: "2023-09"
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end_date: "2024-06"
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tech_stack: Python, PyTorch, CNN, DSP (Hanning Window, Overlap-Add)
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description: 結合數位訊號處理與深度學習的無障礙輔助裝置,旨在還原食道語者的自然語音以解決溝通障礙。
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highlights:
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- "技術實踐:導入 Hanning Window 與 Overlap-Add 技術平滑音訊;使用 PyTorch 訓練 CNN 進行聲學特徵分類,測試集準確率達 86%。"
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- "競賽殊榮:憑藉端到端實作完整度與社會影響力,於通訊工程學系畢業專題競賽中擊敗 17 組團隊榮獲「第一名」。"
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skills:
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- label: "Backend & Systems"
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details: "Python (FastAPI, Pydantic v2, SQLAlchemy v2), RESTful API, Asynchronous Programming"
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- label: "AI & LLM Stack"
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details: "Azure OpenAI (GPT-4o-mini), LangChain, RAG, Text-to-SQL, Few-shot Prompting, Embedding Models"
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- label: "Data & DevOps"
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details: "PostgreSQL (pgvector, RLS), Redis, uv, Docker/Podman, Kubernetes (k9s), Linux, Git, Locust (Load Testing), ETL (Data Sync, Upsert)"
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- label: "Architecture"
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details: "Multi-tenancy, Semantic Caching, Rate Limiting, AST Parsing, SQL Injection Defense"
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certifications:
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- bullet: "**iPAS AI 應用規劃師 (機器學習) 中級** — 2025"
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- bullet: "**TOEIC 720** — 2025"
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design:
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theme: sb2nov
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typography:
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line_spacing: 0.6em
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alignment: justified
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date_and_location_column_alignment: right
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font_family:
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body: LXGW WenKai Mono TC
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name: LXGW WenKai Mono TC
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headline: LXGW WenKai Mono TC
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connections: LXGW WenKai Mono TC
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section_titles: LXGW WenKai Mono TC
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sections:
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allow_page_break: true
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show_time_spans_in:
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- experience
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templates:
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footer: '*NAME -- PAGE_NUMBER/TOTAL_PAGES*'
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top_note: '*LAST_UPDATED CURRENT_DATE*'
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single_date: MONTH_ABBREVIATION YEAR
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date_range: START_DATE – END_DATE
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time_span: HOW_MANY_YEARS YEARS HOW_MANY_MONTHS MONTHS
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experience_entry:
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main_column: |-
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**POSITION**
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COMPANY
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SUMMARY
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HIGHLIGHTS
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date_and_location_column: |-
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LOCATION
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DATE
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normal_entry:
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main_column: |-
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**NAME**
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DESCRIPTION
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HIGHLIGHTS
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*技術棧: TECH_STACK*
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date_and_location_column: |-
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LOCATION
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DATE
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education_entry:
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main_column: |-
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**INSTITUTION**
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AREA
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HIGHLIGHTS
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date_and_location_column: |-
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LOCATION
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DATE
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locale:
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language: mandarin_chinese
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last_updated: 最後更新於
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month: 個月
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months: 個月
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settings:
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current_date: "today"
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