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Mondo User

@mondouser

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QA Automation Engineer at Ever.Ag who built a Windows test framework and cut defects by 50%.

United States

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At Ever.Ag, I built a C# and SQL automation framework from scratch for a Windows desktop application and supported it across releases. I also integrated smoke and full test suites into CI/CD pipelines running in AWS EC2 environments.

By working with product owners on risk-based test coverage, I helped reduce defects by 50% and improve escape rate by 20%. At Intel, I validated internal engineering software and network drivers, and I’m now completing an MEng in Computer Science at Oregon State University.

Experience

Work history, roles, and key accomplishments

Software Engineer - Test Automation

Ever.Ag

Aug 2019 - Oct 2024 (5 years 2 months)

Founding automation engineer for a Windows desktop application, built the test automation framework from scratch in C# and SQL, and maintained it through five years of releases. Reduced defects by 50% and improved escape rate by 20% via a risk-based coverage strategy.

C#SQL CI CD Azure DevOps EC2 Testing Automation Ranorex Selenium Risk Based Testing Mentorship

Software Engineer - Validation & Internal Tooling

Intel Corporation

Jan 2018 - Aug 2019 (1 year 7 months)

Embedded in an agile delivery team building internal engineering software, responsible for feature-level design review, validation logic, and release quality. Improved pre-merge code quality, achieving a 5% reduction in defect rate.

Validation Agile Design Reviews defect reduction Distributed Teams Code Review

Software Engineer - Network Validation

Intel Corporation

Jul 2015 - Jan 2018 (2 years 6 months)

Performed R&D code validation across Intel's commercial network interface card portfolio, ensuring merged driver and firmware code met release standards. Built and maintained Python-based automated regression testing on NIC drivers and firmware.

Python Testing Automation Regression Testing Linux NICs Firmware Technical Documentation

Education

Degrees, certifications, and relevant coursework

Oregon State University

Master of Engineering, Computer Science

Grade: 3.9/4.0

Pursuing a Master of Engineering in Computer Science with a GPA of 3.9/4.0, including coursework in Machine Learning, Deep Learning, NLP, and Applied Cryptography.