Manual QA Engineer – Senior

The SOFTSWISS Game Aggregator is a high-load casino games API platform that connects operator platforms to multiple remote game servers via a single integration. The product is supported by a team of engineers, DevOps specialists, integration experts, account managers, and partnership professionals ensuring reliable, secure, and scalable operations for operators worldwide.

• 4+ years in QA of server-side / backend applications
• Strong test design & analysis: risk-based prioritization, solid test-design techniques, and exploratory testing
• Systematic mindset and independence with proven experience in improving QA processes
• Comfortable in a mixed Scrum / non-Scrum environment
• Strong hands-on experience with microservice-based systems and understanding their trade-offs
• Confident API testing skills with Postman and REST APIs
• Understanding of CI/CD pipelines, specifically GitLab CI
• Experience with bug tracking using Jira including structured defect management and reporting
• Strong troubleshooting skills, able to localize failures (frontend vs backend vs data vs infra)
• Ability to investigate logs and observability tools such as ELK and Grafana
• English / Russian language skills at Upper-Intermediate (B2) level or higher

Nice to have:

• Prior ClickHouse experience
• Web UI testing and familiarity with design systems (component libraries)
• Experience with test automation tools such as Selenium, JUnit, TestNG
• Experience using AI for QA productivity including agents, skills, and LLM tooling
• Experience in Product / iGaming domain

• Own QA for your product team end-to-end: test strategy, checklists, test cases, etc.
• Measure product quality with meaningful QA metrics and indicators (not vanity numbers)
• Report QA status, risks, and plans to your team and product stakeholders
• Review feature requirements early; surface gaps, ambiguities, and risks before development
• Lead releases as the responsible QA; monitor deploy results in production
• Diagnose defects and track them from discovery to resolution
• Validate data directly in the databases
• Collaborate closely with product, infrastructure, and business
• Give product demos to the Product Owner
• Research and adopt new QA approaches and tools, including AI-assisted QA (agents, skills) to speed up routine work
• Continuously improve the team’s QA process