Manual & product QA
Exploratory, functional, smoke, and regression testing. Test design, clear defect reports, and release validation.
Kraków, Poland
Senior QA Engineer who makes releases boring.
Manual, API, and automated testing. Product risks, exploratory testing, and confident release decisions.
AI-assisted QA Claude Code & Codex for test design, debugging, and documentation. See the workflow
About
Five years across manual, general, and automation QA, with experience testing web applications, desktop software, APIs, and WebSockets.
The work spans the testing lifecycle: understanding product risks, designing tests, exploring behavior, reporting defects, validating releases, and building maintainable automation. AI-assisted workflows support analysis, test design, and implementation.
Expertise & tools
Manual exploration, API checks, and maintainable automation across the QA lifecycle.
Exploratory, functional, smoke, and regression testing. Test design, clear defect reports, and release validation.
API and WebSocket testing, business rules, error handling, and defect investigation. Jest, Vitest, and Axios for automated API checks.
UI automation with Playwright and TypeScript. Reusable test code, faster CI feedback, and failure diagnostics.
AI-assisted QA
Daily use of Claude Code and Codex for repository analysis, test design, automation code, debugging, and documentation.
Explore repositories, develop test ideas, and investigate failures with AI assistance. Product risks and existing behavior guide the questions.
Draft and maintain test code, refactor shared utilities, and prepare documentation. Use agents to support repeatable QA work and problem analysis.
Review proposed changes, run relevant checks, and verify behavior manually where needed. Technical judgment stays with the engineer.
Selected work
Selected automation and process improvements from Shelf, alongside the wider manual and general QA experience described below.
Parallel execution and multiple workers sped up many regression CI jobs by up to four times.
Read the CI caseBuilt nearly all automated API checks for one project, with reusable clients, fixtures, and test data.
Read the API caseMaintained and evolved a shared ecosystem of 1,200+ specs and 11,000+ API and UI scenarios.
Read the team caseContext. Long-running regression CI jobs slowed down the feedback cycle, while overnight regression workflows needed ongoing maintenance.
My contribution. Applied parallel execution across many CI jobs, using multiple concurrent workers and other optimizations. Separately, maintained overnight regression workflows for roughly 30 of around 70 CI jobs and investigated failures through logs and test artifacts.
Result. Up to four times faster execution across optimized CI jobs, including a runtime reduction from approximately 60 minutes to 15. These improvements covered many CI jobs, not all jobs or the entire delivery pipeline.
Context. One company project relied on manual API regression work that could be made repeatable.
My contribution. Built nearly all of its automated API checks, using reusable Axios clients, fixtures, helpers, and explicit test-data setup and cleanup.
Result. Reduced repeated manual regression work and left a maintainable basis for future checks.
Context. A TypeScript ecosystem with 1,200+ specs and 11,000+ API and UI scenarios, shared by roughly 10–15 QA engineers, automation engineers, and developers across teams.
My contribution. Maintained and refactored shared code, reviewed changes nearly every day, helped QA engineers and developers use the framework, and created a Datadog dashboard for execution monitoring.
Process ownership. Independently migrated test case management from TestRail to Testomat and created documentation, guidelines, and automation standards.
Result. Better execution visibility and a more consistent way to maintain automation and test case management. The suite size describes the shared ecosystem, not tests authored by me alone.
Jan 2024 – Jul 2026 · Shelf · Remote
Shared automation, CI optimization, API coverage, code reviews, and an independent TestRail-to-Testomat migration.
Oct 2022 – Jan 2024 · Shelf · Lviv
Combined manual product testing and API checks with TypeScript automation, Playwright, Jest, and CircleCI.
Nov 2021 – Oct 2022 · Shelf · Lviv
Manual, API, and WebSocket testing, test documentation, defect reporting, and investigation.
Apr 2021 – Oct 2021 · StarApps · Lviv
Manual web and desktop testing for EV charging and energy-related products.
How I work
Start with what can hurt users or the business, not only what is easiest to automate.
A failed check needs enough context to reproduce, investigate, and decide what to do next.
Clear fixtures, documentation, and a debuggable pipeline matter after the original author moves on.
Engineering notes
Practical ideas behind everyday quality decisions.
Quality engineering
A useful check protects an important behavior and produces a failure someone can act on. If it is flaky or costly to maintain, fix its foundations or reconsider what it is testing. A bigger suite is not automatically a better one.
Exploratory testing
Exploratory sessions follow questions: where do users get stuck, which assumptions fail, and how does the product handle unusual states? Findings become reproducible defects, new test ideas, or candidates for automation.
CI/CD
Only that the checks which ran passed. Trust also depends on what they cover, what was skipped, how failures are investigated, and whether the result arrived soon enough to influence a decision.
Contact
Need help with product quality? Let’s discuss manual testing, API coverage, release validation, and AI-assisted automation.
Manual, general, and automation QA.
Based in Kraków · Open to remote roles