Glilot
Hybrid
Full-time

At Payoneer, quality isn't a gate at the end of the pipeline; it's woven into how teams design, build, and ship. This role is the person who makes that real.

This is a leadership and hands-on role in equal measure. You'll set the quality strategy for large, cross-team features — defining test scope, coverage models, risk areas, and what 'production ready' actually means for each initiative. You'll review developer-written test plans, run E2E and exploratory testing on complex payment flows and microservice integrations, and own post-production validation. You influence architecture from a testability perspective — not as a reviewer, but as a voice in the room when design decisions are made.

AI is changing how quality engineering works, and this role is where that shift happens at Payoneer. You'll use AI tools to accelerate test design, automate triage, scope regressions intelligently, and build QA workflows that didn't exist before. There's no inherited playbook for what AI-assisted QA looks like at fintech scale — you'll write it.

What you'll do:

Own the go/no-go decision for production releases — assess quality readiness, test execution status, and risk posture, and communicate your recommendation clearly to stakeholders
Lead end-to-end quality strategy for large, cross-team initiatives — from planning and design through production monitoring and user journey validation
Define test scope, coverage models, risk areas, rollout strategies, and quality KPIs for complex, multi-team features
Validate complex business flows — payments, integrations, microservices, and event-driven architectures — through E2E, regression, exploratory, and API testing
Use AI tools daily to accelerate test scenario design, defect triage, regression scoping, and coverage analysis — and build the QA workflows that make the whole team faster
Review and approve developer-written test plans; ensure coverage across positive, negative, edge, integration, and failure scenarios
Influence product design and system architecture from a testability perspective — raise quality concerns early, in the design room, not the post-mortem
Mentor developers and QA engineers on testing strategy, automation analysis, and quality best practices; standardize QA methodologies, tools, and processes across teams
Monitor production quality and own post-production validation; track and manage QA technical debt

Who you are:

5+ years in Quality Assurance / Quality Engineering, with meaningful experience in a QA Lead or Senior QA role
Hands-on experience with E2E, regression, exploratory, and API testing across web applications, microservices, and event-driven architectures
Strong SQL — you use it for defect investigation, data validation, and production analysis, not just basic queries
Experience as a QA gatekeeper for production releases — you've made the call under pressure and stood behind it
Hands-on experience with tools such as Postman, Swagger , mock tools, and test management systems
Solid understanding of Agile/Scrum methodologies and CI/CD practices
Experience with production monitoring and post-production validation
Daily use of AI tools to accelerate test design, scenario generation, defect triage, and regression scoping — genuinely fast, not occasional
Clear judgment about when AI-generated coverage is sufficient and when it needs human review and correction
Builds QA workflows and automations with AI assistance — not just individual prompts, but repeatable processes the team can rely on

Advantage:

Familiarity with automation frameworks and hands-on automation execution analysis
Familiarity with cloud infrastructure and cloud-native architectures
MongoDB, Kafka and RabbitMQ experience
Experience in fintech, payments, or other regulated environments

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