Passionate Software Engineer currently with an emphasis on testing frameworks who's is constantly expanding their skillsets in technology.
Experience
New York, New York, United States
As the founding SDET, I architected the end-to-end automation infrastructure for a complex multi-tenant fintech platform. My focus was on shifting from manual scripting to autonomous, generative testing models to support rapid scaling.
Over my tenure at Glide I've accomplished the following:
Model-Based Testing (MBT): Architected a novel graph-based engine that represented the application as a schema. This decoupled test logic from specific UI configurations, allowing us to scale across 1,000+ permutations and 17+ unique tenants.
The "Node-Explorer": Engineered an autonomous discovery tool using Depth-First Search (DFS) to map page states and transitions. This expanded our coverage from a 4-test baseline to 144+ executable user journeys—a 3,600% increase in test coverage.
Scalable Framework: Developed a Playwright + TypeScript POM framework from the ground up, delivering 98+ initial "happy path" suites across Personal, Business, Trust, and Minor account types.
Developer Experience (DX) & Tooling: Built a custom CLI for tenant-switching and automated environment management. Integrated GitHub Pages for live HTML reporting on every PR, providing developers with instant visual traces of test failures.
Infrastructure & Cost Optimization: Implemented API mocking for 3rd-party services like Plaid and Clerk, eliminating external API costs and removing environment-switching bottlenecks.
CI/CD Leadership: Integrated all suites into the CI/CD pipeline with a focus on zero-flakiness and deterministic testing in ephemeral environments.
San Francisco Bay Area
Built and scaled a robust end-to-end test infrastructure for a complex robotics and IoT platform, driving faster, more reliable releases. While officially an SDET, I operated as a full-stack QA engineer and toolsmith, contributing to automation, CI/CD, real-time monitoring, and production frontend features.
Architected a scalable E2E testing framework using Playwright and TypeScript, automating hundreds of critical test cases and significantly reducing platform regressions.
Deployed a real-time telemetry analytics system in DataDog to monitor latency, connectivity, and recovery—vital for field operations.
Built a visual regression tool for analytics dashboards, covering 8,000+ test cases and securing $80K in expansion revenue.
Created CI-integrated tools to provision ROS-enabled turtlebots on-demand and validate agents across ARM/x86 Ubuntu platforms.
Integrated automated tests into GitHub Actions + AWS EC2 runners, reducing costs and improving confidence in releases.
Helped transition release cadence from bi-weekly to on-demand releases through extensive automation and robust pre-deployment validation across staging environments.
Contributed to the React frontend codebase, fixing production UI bugs and developing a new module-grouping feature to enhance dashboard UX.
2022 — 2024
San Francisco Bay Area
As a QA Engineer at Formant, I led and mentored junior QA engineers, promoted best practices in automation and code quality, and coordinated sprint tasks to ensure smooth deployments of high-quality releases on a bi-weekly basis.
2021 — 2022
Plano, Texas, United States
Designed and implemented automated test suites using proprietary automation tools to validate voice assistant functionality, significantly reducing manual testing hours.
Developed Python scripts to parse XML test results and generate HTML dashboards and Excel reports, enabling efficient performance tracking across software releases.
Performed thorough manual testing of voice assistant features to ensure seamless user experiences in next-generation Toyota vehicles.
Leveraged Spanish language proficiency to test and identify issues specific to the Spanish-language voice assistant interface.
2019 — 2020
Tulsa, OK and Surrey EG
Tested and trained multiple machine learning models to troubleshoot errors in mobile networks in project between Oklahoma University in Tulsa, Oklahoma, and University of Surrey in Guildford, England.
· Delivered a unique machine learning solution that improved accuracy of models performing fault diagnosis of referenced signal received power cellular heatmaps.
· Discovered positive results and methods within a short duration of time that increased accuracy over prior approaches.
· Used technical writing abilities to successfully publish a paper regarding my findings into the IEEE BlackSeaCom 2020 conference.
· Presented and discussed results clearly in front of a technically inclined audience.
Education
The University of Texas at Dallas