Chloe

about

I'm a software and AI engineer at J.P. Morgan Chase, where I build LLM applications, retrieval systems, and backend data platforms. I specialize in helping people query and understand enterprise data through grounded text-to-SQL workflows, hybrid search, and AI-powered tools. My experience includes building Python orchestration for LLM reasoning and tool use, combining PGVector and BM25 retrieval, and creating embedding pipelines for table, column, and field-value metadata. I also develop DynamoDB-backed governance workflows, improve production observability with Datadog, and implement deployment pipelines using AWS ECS, Docker, Terraform, and CI/CD tools. I've initiated an AI metadata documentation assistant to reuse existing field definitions and generate human-reviewable documentation drafts. I've also built a feedback analysis assistant with chatbot Q&A and interactive dashboards. Earlier, as a data science intern, I trained and deployed machine learning models to classify application screens for a customer-service AI platform. I can help with RAG applications, semantic search, text-to-SQL systems, metadata automation, Python backend development, and cloud deployment. I hold a Master of Computer Science from the University of Illinois at Urbana-Champaign.