AI 產品工程師 (AI Product Engineer)

【必備條件】

• 具備全端開發能力,能 own 一個 feature 從 UI 到 API 到資料庫
• 網頁開發基本功紮實(響應式、accessibility、API 設計),不執著特定技術棧 — 能透過 AI 工具快速適應新框架
• 熟悉 Git / 版本控制流程(branch 管理、PR/MR 流程)
• 對資料模型與儲存方案有判斷力 — 能根據需求選擇合適的方案(SQL / NoSQL / cache 等)
• 熟悉雲端部署與容器化(Docker / Kubernetes),對服務架構拆分有判斷力(monolith vs 微服務)
• 具備 background jobs 與 async / event-driven 處理經驗
• 善於活用 AI coding 工具(Claude Code、Codex、Cursor、GitHub Copilot 等)與 Prompt 提升開發效率
• 具備產品 trade-off 思維與跨職能協作能力

【加分項目】

• 對前端 UI craft 有要求 — 重視視覺一致性、互動細節與 accessibility,能用 AI 工具快速產出介面並迭代到 production 品質
• 對自動化部署與可觀測性有實作經驗(CI/CD、monitoring),重視流程自動化與系統健康可見度
• 熟悉系統與 API 安全(OAuth2、JWT、OWASP),並對 AI 應用安全有概念(prompt injection、agent safety、敏感資料外洩等)
• 具備高流量或可擴展系統設計經驗(Scalability / Reliability / Observability)
• 熟悉事件驅動架構或即時通訊開發(message queue、pub/sub、WebSocket 等)
• 曾參與大型專案、開源貢獻或有個人 Side Project
• 做過 LLM 整合的產品 feature(chatbot、summarization、agent 等)
• 熟悉 prompt engineering、RAG (Retrieval-Augmented Generation) 架構與向量資料庫(Qdrant / Pinecone / Weaviate 等)
• 對 agentic 應用設計有概念(tool use、memory、evals)

【團隊文化與福利】

• 彈性工作文化:信任與責任並重
• 核心工時 10:30 ~ 16:30,中午可彈性休息 1 小時,其餘時間可自由安排
• 每月提供遠端工作申請額度(可異地 / 海外)
• 團隊定期 Tech Sharing / 讀書會,共同精進技術
• 提供 線上課程 / 專業證照補助,支持持續學習
• 提供 AI 工具訂閱津貼(如 ChatGPT、Claude、Codex、Cursor 等),幫助提升開發與研究效率
• 跨領域合作:與前端 / 後端 / App / AI 團隊緊密協作
• 扁平化組織,意見能快速落地,每個人都能影響產品方向
• 全新商辦大樓辦公環境,舒適明亮、交通便利
• 配備雙螢幕、全新 MacBook Pro、升降桌與人體工學椅,打造高效能、舒適的工作環境
• 公司不定期提供 飲料零食,提升工作活力
• Team Building 活動(公司聚會 / Hackathon / Workshop)

⸻

Required Qualifications

• Full-stack capable — able to own a feature end-to-end from UI to API to database
• Solid web development fundamentals (responsive design, accessibility, API design) — not tied to a specific stack, able to ramp up on new frameworks quickly with AI tools
• Proficient with Git / version control workflows (branch management, PR/MR flow)
• Strong judgment on data modeling and storage choices — able to pick the right solution (SQL / NoSQL / cache, etc.) based on the use case
• Familiar with cloud deployment and containerization (Docker / Kubernetes), with judgment on service architecture decisions (monolith vs microservices)
• Hands-on experience with background jobs and async / event-driven processing
• Skilled in leveraging AI coding tools (Claude Code, Codex, Cursor, GitHub Copilot, etc.) and prompts to boost development efficiency
• Strong product trade-off thinking and cross-functional collaboration skills

Nice to Have

• Strong sense of frontend UI craft — values visual consistency, interaction details, and accessibility; able to use AI tools to rapidly generate UIs and iterate to production quality
• Hands-on experience with deployment automation and observability (CI/CD, monitoring), with a focus on workflow automation and system health visibility
• Familiar with system and API security (OAuth2, JWT, OWASP), with awareness of AI application security concerns (prompt injection, agent safety, sensitive data leakage, etc.)
• Experience with high-traffic or scalability-aware system design (Scalability / Reliability / Observability)
• Familiar with event-driven architectures or real-time communication (message queue, pub/sub, WebSocket, etc.)
• Previous experience in large-scale projects, open-source contributions, or personal side projects
• Have shipped LLM-integrated product features (chatbot, summarization, agent, etc.)
• Familiar with prompt engineering, RAG (Retrieval-Augmented Generation) architectures, and vector databases (Qdrant / Pinecone / Weaviate, etc.)
• Conceptual understanding of agentic application design (tool use, memory, evals)