Biying Zhang is a Senior AI Engineer based in California with 11 years of experience building cloud-native, production-ready AI workflows that bridge distributed systems and full-stack web development. She specializes in deploying low-latency inference pipelines and multi-agent systems—recently delivering a fraud-detection platform that cut manual verification calls by 90% using a hybrid of hard rules and RAG-powered LLM scoring. Comfortable across Python, TypeScript, FastAPI, Next.js and major cloud providers (GCP, AWS, Azure), she designs event-driven architectures with careful data validation, immutable audit logging, and model-switching patterns to keep systems auditable and provider-agnostic. Her background in fine arts informs a curiosity-driven approach to product design and user experience, evident in prior work that blended visualization and engineering for research and marketing use cases. Certified across LangChain/LangGraph and advanced ML specializations, she pairs hands-on model work (PyTorch, DeBERTa) with robust CI/CD and observability practices to move prototypes safely into scale.
11 years of coding experience
7 years of employment as a software developer
Master of Fine Arts (M.F.A.), Fine and Studio Arts, Master of Fine Arts (M.F.A.), Fine and Studio Arts at Tufts University
Bachelor of Fine Arts, Fine/Studio Arts, General, Bachelor of Fine Arts, Fine/Studio Arts, General at The Central Academy of Fine Arts
TDD, BDD, built with Ruby on Rails, FactoryBot, RSpec, Capybara and Cucumber, deployed on Heroku
Contributions:84 commits, 30 PRs, 402 pushes in 4 years 9 months
bddcucumberfactory-botherokurspec
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