We’re looking for a detail-oriented and proactive QA Engineer to ensure the quality and reliability of our products. You’ll take ownership of testing processes, collaborate closely with developers and product teams, and help deliver seamless user experiences. If you’re passionate about quality, enjoy solving complex problems, and want to make a real impact — we’d love to meet you.
Requirements:
Proven ability to lead, organize, and mentor QA teams of different sizes, including setting priorities, distributing workload, and enforcing quality standards
Experience designing and executing performance/load/stress tests, interpreting metrics, and collaborating with engineers to resolve bottlenecks
Experience testing products in the fintech domain, with awareness of data integrity, and critical financial scenarios
Experience testing complex distributed systems based on microservices of different types and architectural styles, including validation of inter-service communication, resiliency, observability, and end-to-end system behavior.
Responsibilities:
Technology stack
Frontend – Typescript (NextJS, React, Vue)
Network core – Rust
Ecosystem applications/projects – Typescript/Javascript (NestJS mainly), some of the components written in Golang/Rust
Infrastructure stack – on-premise, Azure, AWS (everything runs in Kubernetes clusters)
Lead QA activities for the account, ensuring consistent quality standards and alignment with client and project goals.
Report progress and quality status regularly to stakeholders, highlighting blockers, risks, and proposed mitigation actions.
Identify, propose, and implement new QA practices, approaches, and process improvements across the account.
Review and resolve critical situations and conflicts related to quality, processes, or collaboration within the team.
Take an active, hands-on role in testing for at least one project within the account, especially for complex or high-risk areas.
Support discovery activities and onboarding of new projects, contributing to test strategy, estimations, and risk assessment.
Define, collect, and analyze quality metrics and risks, and use them to drive data-informed decisions and improvements.
Investigate and analyze complex parts of the product from a testing perspective, identifying gaps, edge cases, and optimal test approaches.
