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ZHIYONG JIANG
Senior AI & Machine Learning Engineer specializing in GenAI, Agentic AI, and RAG
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About
Built a production agentic AI system to automate data science work using a layered architecture (executive-summary handling, tool-based execution, and on-the-fly code generation). Demonstrates strong end-to-end agent development practices including RAG with vector databases, prompt engineering, and multi-method evaluation (LLM-as-judge/human/code-based), plus Airflow-based orchestration for ML data pipelines and close collaboration with business end users.
Experience
Education
Key Strengths
- Built and deployed an agentic AI system to automate data science tasks
- Layered agent architecture (summary layer, tool-using layer, code-generation layer)
- Structured approach to agent design grounded in business goals and functional/non-functional requirements
- Comprehensive evaluation strategy (LLM-as-judge, human eval, code-based eval) across components like routing and code generation
- Pragmatic model selection balancing accuracy, latency, and cost (high-end models for critical tasks/evaluation; cheaper models for less critical components)
- Workflow orchestration experience using Apache Airflow for scheduled ML/data processing pipelines
- Effective collaboration with non-technical business stakeholders via regular check-ins, demos, and user enablement
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