Summary
Xiaowan Li is an SDE II based in Seattle with a decade of engineering experience and over six years at Amazon building distributed backend platforms for workforce planning, ML infrastructure, and high-throughput data ingestion. She designs canonical data models, APIs, and metric computation libraries that power hierarchical planning for millions of employees and standardized workforce metrics across global organizations. Xiaowan led scalable ML metadata platforms ingesting and governing 1.3M+ artifacts, re-architecting ingestion from Lambda to AWS Batch for stronger idempotency and operational guarantees, and integrated OpenSearch for fast artifact discovery. Her work spans privacy- and compliance-sensitive systems—GDPR-safe event persistence and SQS/DLQ redesigns that eliminated a 100K+ message backlog—and she routinely serves as acting tech lead coordinating cross-org delivery. Trained in NLP and data management, she combines academic rigor with practical system design and mentors junior engineers on DynamoDB modeling and scalable API patterns. An ability to translate ambiguous, cross-functional requirements into production-ready, observable systems is a recurring strength in her career.
10 years of coding experience
2 years of employment as a software developer
Master's degree Natural Language Processing (NLP AI), Master's degree Natural Language Processing (NLP AI) at Nanjing University
The University of Utah
Bachelor of Engineering - BE Computer Science and Engineering, Bachelor of Engineering - BE Computer Science and Engineering at Soochow University (CN)
Chinese, English