About the company
Founded in 2005, Payoneer is the global financial platform that removes friction from doing business across borders, with a mission to connect the world’s underserved businesses to a rising global economy. We’re a community with over 2,500 colleagues all over the world, working to serve customers, and partners in over 190 countries and territories.
By taking the complexity out of the financial workflows–including everything from global payments and compliance to multi-currency and workforce management, to providing working capital and business intelligence–we give businesses the tools they need to work efficiently worldwide and grow with confidence.
Responsibilities
- Quality Gatekeeping: Make the go/no-go decision for production releases. Assess quality readiness, test execution status, and risk posture. Communicate your recommendation clearly to stakeholders. Own the decision under pressure.
- End-to-End Quality Strategy: Lead quality planning for large, multi-team features—from design review through production validation. Define test scope, coverage models, risk areas, quality KPIs, and rollout strategies. Influence product design and system architecture from a testability perspective.
- Hands-on Testing & Technical Investigation: Execute E2E, regression, exploratory, and API testing across web applications, microservices, and event-driven architectures. Use SQL for defect investigation, data validation, and production analysis. Debug complex interactions between microservices in a fintech environment.
- Test Plan Review & AI Audit: Review and approve developer-written test plans; ensure comprehensive coverage across positive, negative, edge, integration, and failure scenarios. Audit AI-generated test coverage and correct it when it misses business logic or fintech-specific risks.
- AI-Assisted Workflow Building: Use AI daily to accelerate test design, scenario generation, defect triage, and regression scoping. Build repeatable QA workflows and automations with AI assistance. Establish when AI-generated coverage is sufficient and when it needs human review.
- Mentorship & Quality Culture: Elevate the testing and quality mindset across engineering teams. Mentor QA engineers and developers on testing strategy, automation, and quality best practices. Standardize QA methodologies, tools, and processes across teams.
- Production Monitoring & Multi-Region Validation: Own post-production quality validation and monitor for unexpected behaviors or regressions. Understand how product variations, regional regulations, and local infrastructure affect quality. Plan testing for features that must comply with RBI, GST, FEMA, and other India-specific requirements.
Requirements
- Minimum 5+ years of QA/Quality Engineering experience, with meaningful experience as a QA Lead, Senior QA Engineer, or Test Manager.
- Hands-on testing expertise in E2E, regression, exploratory, and API testing across web applications, microservices, and event-driven architectures.
- Strong SQL skills: You use SQL for defect investigation, data validation, and production analysis—not just basic queries.
- Production release experience: You have made go/no-go decisions under pressure and owned those decisions.
- Tool proficiency: Postman, Swagger, mock tools, and test management systems (TestRail, Jira, etc.).
- Agile & CI/CD: Solid understanding of Agile/Scrum methodologies, sprint cycles, and CI/CD pipelines.
- Post-production monitoring: You validate quality after features go live and know how to identify issues using production data.
- Daily AI tool usage: You use AI to accelerate test design, scenario generation, and regression scoping. You have sound judgment on when AI-generated coverage is sufficient and when it requires human review.
- AI-assisted workflow building: You have built repeatable QA workflows and automations using AI—not just one-off prompts.
- Clear communication in English: You communicate effectively with technical and non-technical stakeholders, both locally and globally.
- Business acumen: You communicate in terms of risk and business impact, not just test metrics.
- Collaboration: You work effectively across teams and influence without formal authority.