At Intuit Inc., I work on benefits eligibility services where secure workflows and dependable behavior after release matter. I revised the TypeScript eligibility decision flow to separate rules evaluation from application state transitions, and tested conflicting household inputs.
I also built a controlled approach to benefits data reconciliation in Python, comparing system-of-record changes with derived eligibility indicators and flagging mismatches for human review. Across unchanged review cases, investigation time fell from 91 to 61 minutes, supporting a 30%+ reduction.
Across my work at Intuit Inc., Stripe Inc., Salesforce Inc., and Google LLC, I’ve focused on service contracts, failure recovery, and privacy-conscious backend systems. I document assumptions and release safeguards so teams can reproduce failures and maintain systems without relying on the original author.
