Kevin Lin

Engineered AI-powered invoice classification and automation pipelines, reducing manual processing by 80% and cutting cycle time from 5 days to 10 hours. Built high-throughput ingestion and validation services achieving <500ms latency and $1M+ annual cost savings, while improving accuracy to 99.8% and accelerating incident resolution by 30%.

Developed AI-assisted validation frameworks for Workday integrations, reducing payroll and HR system failures by 80%. Architected event-driven pipelines for journal entry creation and reconciliation, cutting month-end close from 8 days to 4 days and improving reporting accuracy by 30%.

Delivered reusable libraries and tools that reduced development time for financial automation projects by 40%. Designed logging and monitoring for pipeline performance and system health, reducing incident response time by 30%, and led knowledge-sharing sessions to improve adoption.

Maintained high-availability backend services for enterprise financial applications, improving data accuracy and interoperability via robust API services. Automated financial reporting and reconciliation (reducing report generation time by 60%), built data validation pipelines (improving reliability by 25%), and optimized ETL/database performance to increase transaction throughput by 40%.

Earned a bachelor’s degree in computer science at Rutgers University from 2012 to 2016.