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Software QA Engineer/Intern (AI-Powered)

internofficeТашкент, UZScore undefined/1001d ago
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📊 QA / Testing: salaries and demand on the market
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ci/cdgojavajavascriptplaywrightselenium
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Description
Finishing your degree and not sure what's next? Turn your CS education into a real engineering career - starting now. You've spent years studying algorithms, data structures, and software design. You've written code for coursework and side projects. Now you need a way into the industry that actually values what you've learned - without requiring years of experience you don't have yet. This is that way in. Not manual testing, not "click around and file tickets" - a full-spectrum QA Engineer role where you write real automation code, work in real repositories, go through real code review, and apply the CS fundamentals you already have to a discipline that's still hungry for technical talent. You'll also work with AI daily - for writing code, generating test data, and analyzing requirements - while learning where it gets things wrong, because it will. What You Need A degree (or final year of study) in Computer Science, Software Engineering, or a related technical field JavaScript/Java knowledge at a junior developer level Solid grasp of Object-Oriented Programming (OOP) fundamentals English level B1 or higher 40 hours/week available for training, internship, and the role that follows Based in Tashkent Why This Path Makes Sense for CS/Engineering Grads Your coursework in programming, OOP, and problem-solving translates directly - this isn't a career change, it's a launch point A structured, 4-5 month mentoring program that turns academic knowledge into professional engineering skills A real bridge into full-time employment, not a temporary gig AI-first workflow from day one, learning both its power and its limits What You'll Learn Automation with Playwright/Selenium - real code, real repos, real review API testing, databases, logs, CI/CD pipelines Test design, requirements analysis, exploratory testing of complex business logic Where AI tooling helps in QA - and where it can't be trusted What Happens After
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