QA Engineer

About this role

Senior QA Engineer (TradeZella product) We're looking for a QA Engineer who cares about product quality end-to-end, someone who gets trading through real experience, professional or personal. Trading doesn't need to be your career; a hobby or a past chapter counts, but long-term investing alone doesn't. You'll join TradeZella , our trading journaling and educational platform, and focus on how the product works in real conditions: testing functionality, investigating edge cases, and resolving complex issues together with engineering, product, and support teams.

This role requires a genuine interest in the trading domain, along with strong UX testing skills. What are we looking for? Testing & QA expertise: Strong experience with manual testing and end-to-end validation Solid UX testing skills beyond formal requirements (user acceptance testing, business acceptance testing, usability validation) Hands-on day trading experience (any market: stocks, forex, futures, crypto), past or present, professional or personal, with the ability to walk us through at least one strategy you've traded Experience in investigating customer issues and performing root cause analysis Experience in building and improving QA processes Technical skills: Strong debugging and problem-solving skills, including log analysis (CloudWatch, Logs Explorer) Good understanding of networks, HTTP, APIs, and web/client architectures Experience with version control systems (GitHub, GitLab, etc.) Experience using AI tools for workflow optimization Communication & mindset: Ability to translate technical concepts for different audiences (engineering ↔ non-technical) Strong sense of ownership and accountability Structured, detail-oriented approach Fluent English (written and spoken) Would be a plus: Experience with Playwright (TypeScript) Your responsibilities Analyze requirements, test functionality, and identify defects, confusions, and edge cases Own investigation of complex customer issues through L3 support, driving root cause resolution Partner with engineering and product to resolve issues and improve system reliability Improve QA practices and elevate debugging and investigation standards, including AI adoption practices Support releases and ensure stable rollouts with active post-release follow-up Support and extend existing AI agents and skills to make the QA process more efficient