I'm a software engineer based in Seattle working on distributed backend infrastructure where correctness isn't a nice-to-have — it's the whole job. Currently at AWS, working on infrastructure, security, and reliability for global tax computation systems.
I graduated from the University of Arizona with a B.S. in Software Engineering and now work at AWS on tax and invoicing infrastructure that processes millions of transactions worldwide — a domain where a single bad computation has real financial consequences, so correctness and reliability come first in everything I build.
That same instinct for correctness shows up across my work: from formally verifying tax rule changes with SMT solvers, to designing idempotent APIs that can never double-charge a customer, to leading my senior capstone team in building an AI-assisted patient monitoring system alongside biomedical and computer engineers. I like problems where being "mostly right" isn't good enough.
Architecting core infrastructure for tax computation systems, leading international workflow migrations, and building AI agent tooling adopted across my team.
Designed and built ETL data integration pipelines between Salesforce CRM and university systems, synchronizing PII and academic records for 50K+ students across multiple data sources.
Built a rule evaluator using SMT solvers to formally verify tax rule engine changes before deployment, processing ~2.25M rule evaluations per configuration deployment.
Owned the infrastructure foundation — networking, security, reliability, and idempotency — for a platform computing tax on cloud transactions worldwide.
Read case study →Led the migration of live international tax workflows onto modernized infrastructure, reducing rounding issues and increasing calculation accuracy.
Read case study →Authored the high- and low-level designs to consolidate dual invoicing into a unified customer experience across international markets, including Brazil.
Read case study →Built a formal verification tool that catches tax rule regressions before deployment, processing ~2.25M rule evaluations per release.
Read case study →Built and drove team-wide adoption of a suite of AI agent skills that automate operational and development workflows.
Read case study →Senior capstone project: an AI-assisted exam room that tracks patient movement, mood, and speech to help doctors catch what a visit might miss.
Read case study →Based in Seattle, WA. Open to connecting about roles, systems, or anything correctness-critical.