Product Engineer · Co-Founder & CTO
Building reliable products for real operations.
I work directly with users and operators to turn complex workflows into reliable full-stack software, then stay accountable through testing, release, recovery, and production improvement. At Red Eye Tickets, I rebuilt a WordPress MVP as a Rails, React, and PostgreSQL event-commerce platform spanning payments, inventory, ticketing, producer tools, and live admissions.
Production lifetime snapshot as of September 11, 2026 at 3:51 PM PDT: $1.44M+ in customer charges processed · 28.5K+ paid orders · 19.1K+ unique buyers.
Production scale
Red Eye Tickets in production.
A live event-commerce platform supporting the customer journey from checkout through venue admission.
Production totals through September 11, 2026 at 3:51 PM PDT · Metric definitions →
Engineering evidence
How reliability is designed, tested, and recovered.
Case studies and technical artifacts showing how the product handles real money, scarce inventory, production failures, and controlled automation. Each item is labeled by maturity and evidence boundary.
Production integration
One checkout across three payment protocols
How Authorize.Net, Apple Pay, and Google Pay share authoritative order state while preserving provider-specific validation, order-bound idempotency, webhook recovery, and reconciliation.
Payments · Idempotency · ReconciliationRead the Payment Case Resolved production incidentThe final ticket was held, but capture counted it twice
How a guest's own final-inventory hold became competing demand after confirmation associated the order with an existing account—and how origin-bound ownership fixed it without weakening capacity safety.
Checkout origin · Inventory integrity · 6,706 backend examplesRead the Incident Review Production incidentThe event title that broke ticket PDFs
How one valid emoji exposed an encoding boundary across stored event data, fonts, and PDF rendering, and how the fix was protected against recurrence.
Incident response · Root cause · Regression coverageRead the Incident Review Production reliabilityTesting, release, and recovery
How RSpec, Jest, Playwright, risk-based CI gates, production canaries, exact-commit releases, rollback, and post-deploy verification protect critical workflows.
Automated testing · Release safety · VerificationReview the Reliability Controls Guarded prototypeAI-assisted production repair with explicit boundaries
How signed operational evidence becomes bounded repair work through separate planning, execution, review, policy, approval, rollback, and verification stages.
Human approval · Safety gates · Maturity limitsExplore the Guarded ArchitectureSelected work
Product engineering, technical tools, and coded interaction.
Work across event commerce, 3D research visualization, and design engineering.
View All Work
Product Engineering
Red Eye Tickets
Built and operate a Rails, React, and PostgreSQL event-commerce platform where payments, inventory, ticket delivery, and venue admission must remain in sync.
Co-Founder & CTO · Sole technical contributor · January 2024–present
Custom platform launched October 2025
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3D Research Visualization
Albert Einstein College of Medicine
Recreated a professional glTF and meshoptimizer workflow as a public Three.js demo with progressive LOD loading, caching, structure controls, and live measurement.
Contract Frontend Developer · May 2023–January 2024
Scoped contributionPublic-data recreation
Interactive 3D demoOperating style
From ambiguity to a system people can trust.
I move from workflow discovery through implementation, release, production verification, and learning.
Map the real workflow
I start with the people, handoffs, constraints, and moments where work breaks down.
Turn ambiguity into structure
I convert loose goals into user flows, product decisions, implementation plans, and usable interfaces.
Ship systems people trust
I care about whether the system is clear, reliable, maintainable, and practical for the people using it.
Open to Product Engineer, workflow-oriented FDE, and coding-heavy AI implementation roles. Remote preferred; New York or San Francisco relocation available.
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