About Me
I'm a Staff SDET, a Software Development Engineer in Test. I've spent that career on quality engineering, test architecture, and more recently on AI-augmented development. I know where a test belongs in the pyramid, and what it takes to release quickly without crossing your fingers. The work I keep coming back to is building test infrastructure that scales, getting quality treated as everyone's job across an engineering org, and putting the newer AI tools to work on how fast a team can move.
Core Competencies
Test Strategy & Architecture
- Test Pyramid Design
- Unit & Component Testing
- Integration Testing
- E2E Test Automation
- Visual Regression Testing
- LLM Evaluation Testing
- Performance & Load Testing
- Contract Testing
Testing Techniques
- Mocking & Stubbing
- Test Doubles & Fakes
- Snapshot Testing
- Data-Driven Testing
- Shift-Left Testing
- Mutation Testing
- Accessibility Testing
Frameworks & Tools
- Playwright
- Cypress
- Selenium
- Storybook
- Jest / Vitest
- Testing Library
- Appium
- k6 / Artillery
Languages
- JavaScript / TypeScript
- Python
- Java
- Node.js
- PHP
- .NET / C#
- SQL
AI & Developer Tools
- Claude Code
- Cursor IDE
- GitHub Copilot
- LLM Eval Frameworks
- MCP Servers
- Development Context Repos
- Prompt Engineering
CI/CD & Infrastructure
- GitHub Actions
- Jenkins
- Docker
- AWS
- Terraform
- Kubernetes
APIs & Services
- REST API Testing
- GraphQL
- gRPC
- OpenAPI / Swagger
- Postman / Newman
- API Mocking
Databases
- PostgreSQL
- MySQL
- MS SQL Server
- MongoDB
- Redis
My Approach to Testing
Testing is worth being strategic about, for quality and for efficiency both. The pyramid is how I get there: the right balance of unit, integration and end-to-end tests, so you're getting the most coverage for the least overhead.
What I'm after is teams that can ship confidently without slowing down to do it. That comes down to automating the right things, keeping test suites maintainable, and making sure that when something does fail, the feedback is clear enough to act on.
AI-Augmented Quality Engineering
AI and quality engineering is where most of my attention goes at the moment. I maintain a development context repository so that AI coding assistants understand the project architecture, the testing patterns and the team's conventions before they write anything. It speeds up development cycles dramatically, and it does that without giving up any ground on quality.
On the evaluation side, I build frameworks that assess LLM output for accuracy, consistency and safety in a systematic way. It's a young discipline that takes the traditional testing principles and adds evaluation methods built for systems that aren't deterministic.
What Sets Me Apart
I sit between software engineering and quality. Finding bugs is part of that, but the larger part is architecting systems that keep them from happening. I come at testing as a developer, building the tools and frameworks teams actually want to use. That's covered the full stack, from component-level Storybook testing and visual regression through to production observability and incident response.
I've led quality initiatives across several product teams, mentored engineers on testing practice, and built test infrastructure that holds up from startup scale to enterprise. I do my best work where quality is a shared responsibility and the team still cares about moving fast.