Microsoft AI Architect/Developer 

Taiwan, Taoyuan City 

713656025

• Master’s degree (or higher), preferably with a specialization in Machine Learning, Data Science, or AI.
• Minimum 10+ years as a technical solution architect or consultant with proven expertise in AI/ML development.
• Mandatory hands-on experience in Python development, with extensive practical experience building and deploying production-grade AI solutions.
• Proven track record of successful delivery of cloud-native AI projects, ideally on the Azure platform.
• Demonstrated expertise in deep-learning and Agentic AI frameworks ( Semantic Kernel, LangChain, LangGraph etc.) and model optimization.

Preferred Qualifications:

• Additional, hands-on software development experience in JavaScript and/or .NET , providing full-stack solution design capability.
• Deep understanding and practical experience with Azure OpenAI (e.g., ChatGPT, DALL·E 2), Azure ML, and AI Agent development frameworks.
• Expertise in implementing automated deployments using Azure DevOps, GitHub (CI/CD pipelines) and comprehensive understanding of MLOps practices.
• Excellent communication skills (written and verbal) with the ability to articulate complex technical solutions clearly to diverse audiences, including senior executives.
• Strong analytical and problem-solving skills, with a passion for customer empathy and user-centric solution design.

• Lead hands-on design and development efforts primarily using Python , building robust, scalable, and customer-focused AI/ML solutions.
• Engage directly with key enterprise customers to strategize, architect and implement AI driven, Agentic AI solutions leveraging Azure AI services including Azure OpenAI, Azure ML.
• Translate complex requirements into practical, well-architected technical solutions.
• Develop end-to-end, rapid prototypes, involving data ingestion, validation, processing, and model deployment using Azure platform components.
• Build, customize, and optimize AI models and related components for customer-specific use cases.
• Integrate AI solutions with full-stack architectures, preferably leveraging experience with JavaScript frameworks (e.g., Node.js, React) and/or .NET ecosystems .
• Establish and maintain robust CI/CD and ML Ops pipelines, leveraging Azure DevOps, Github for automated deployments.
• Proactively explore diverse datasets to engineer novel features and signals that significantly enhance ML performance.
• Participate actively in every phase of the model lifecycle from conceptualization, training, fine tuning, validation, and deployment, to continuous monitoring and improvement .