Gary Chang

About

End-to-end engineer who has productionized AI automation and RAG capabilities, building full-stack systems (React/Node/Redis/Postgres + vector DB) with evaluation-driven quality gates and monitoring. Reported ~60% reduction in manual ops time and major turnaround improvements, and has experience modernizing legacy systems safely via feature flags and parallel runs while working across product, data, and ops teams (System1).

Key Strengths

• Owned and shipped end-to-end AI workflow automation across frontend, backend, data, and infrastructure
• Delivered measurable ops impact: ~60% reduction in manual processing time; hours-to-minutes turnaround improvement
• Productionized AI systems with rigorous evaluation gates (test dataset, quality thresholds) and ongoing quality monitoring
• Designed scalable async orchestration using Redis queues and service APIs
• Built RAG assistant over internal docs/databases with grounding, confidence thresholds, and no-answer fallback guardrails
• Modernized legacy systems incrementally using stable APIs, feature flags, and parallel runs to avoid regressions
• Strong cross-functional execution across product/data/ops with tight feedback loops, demos, and lightweight documentation
• Effective use of AI dev tools for faster system understanding, refactoring, and debugging (log/trace-driven RCA)

Experience

Education

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