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Key Responsibilities

AI-Powered Test Solution Development & Integration:
- Design, develop, and maintain innovative AI-driven testing programs and applications using Google AI APIs.
- Develop backend services and APIs using Python, Google App Script, and HTML5, ensuring high standards for code quality, performance, and scalability.
- Collaborate closely with the testing team to ensure experimental models align with practical testing scenarios and operate stably.

System Architecture & Integration:
- Design and manage scalable database architectures, including relational and vector databases, based on application requirements.
- Design and implement a robust integration layer between backend AI services and Android applications, ensuring efficient and reliable API communication.

Quality Assurance & Process Optimization:
- Develop and maintain a comprehensive automated testing framework, covering unit, integration, and end-to-end tests.
- Establish automated testing pipelines to ensure the stability and quality of AI applications through continuous iteration.

Qualifications

Qualifications
- Python Development:
Solid experience in Python development, with a strong understanding of the software development lifecycle and API design principles.
- Web Technologies
Proficiency in Google App Script and HTML5 development.
- Android Architecture
A deep understanding of the Android application lifecycle, core components, and modern Android development architecture patterns (e.g., MVVM, MVI).
- Google AI APIs
Experience with or high-level familiarity with Google AI services (e.g., Vertex AI, Gemini API).
- Generative AI Knowledge
A thorough understanding and practical experience with Generative AI, Large Language Models (LLMs), and RAG principles.
- Familiarity with the design and SQL operations of relational databases (e.g., PostgreSQL, MySQL) and a basic understanding of vector databases.
- Experience in designing and implementing software testing strategies, with knowledge of the purposes and methods of different testing levels.
- Ability to clearly articulate complex technical concepts to both technical and non-technical stakeholders.
- Excellent English reading and writing skills for independently reviewing technical documentation and for written communication.
- Proven ability to independently analyze, diagnose, and resolve complex technical issues.

Preferred Qualifications:
- 3+ years of professional development experience.
- Familiarity with Python testing frameworks (e.g., Pytest, Unittest).
- Proficiency with a Python web framework (e.g., FastAPI, Flask, Django).
- Experience with containerization technologies (e.g., Docker).
- Experience with Android automated testing frameworks (e.g., Appium).
- Experience in hardware integration and programming (e.g., using Arduino,
- Raspberry Pi for robotics control or IoT device development).

Long Description

AI 驅動測試解決方案開發與整合：
使用 Google AI API 設計、開發並維護創新的 AI 測試程式與應用程式
使用 Python、Google App Script 和 HTML5 開發後端服務與 API，確保程式碼品質、效能與可擴展性
與測試團隊密切合作，確保實驗模型符合實際測試場景並穩定運作

系統架構與整合：
根據應用需求設計並管理可擴展的資料庫架構，包括關聯式與向量資料庫
設計並實作 AI 後端服務與 Android 應用程式之間的整合層，確保 API 溝通高效且可靠

品質保證與流程優化：
建立並維護完整的自動化測試框架，涵蓋單元測試、整合測試與端對端測試
建置自動化測試流程，透過持續迭代確保 AI 應用的穩定性與品質

資格條件：
- 具備紮實的 Python 開發經驗，熟悉軟體開發生命週期與 API 設計原則
- 熟悉 Google App Script 與 HTML5 開發
- 深入了解 Android 應用程式生命週期、核心元件與現代架構模式（如 MVVM、MVI）
- 具備使用 Google AI 服務（如 Vertex AI、Gemini API）的經驗或高度熟悉度
- 深入理解並具備生成式 AI、LLM（大型語言模型）與 RAG（檢索增強生成）原則的實作經驗
- 熟悉關聯式資料庫（如 PostgreSQL、MySQL）的設計與 SQL 操作，並具備向量資料庫的基本認識
- 具備設計與實作軟體測試策略的經驗，了解各種測試層級的目的與方法
- 能清楚向技術與非技術利害關係人說明複雜技術概念
- 具備優秀的英文閱讀與書寫能力，能獨立閱讀技術文件並進行書面溝通
- 具備獨立分析、診斷與解決複雜技術問題的能力

加分條件：
- 3 年以上專業開發經驗
- 熟悉 Python 測試框架（如 Pytest、Unittest）
- 熟悉 Python Web 框架（如 FastAPI、Flask、Django）
- 具備容器化技術經驗（如 Docker）
- 熟悉 Android 自動化測試框架（如 Appium）
- 具備硬體整合與程式設計經驗（如使用 Arduino、Raspberry Pi 進行機器人控制或 IoT 裝置開發）

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