Lead Quality Engineer

We are looking for a hands‑on Quality Engineer to help rebuild and modernize our test automation capabilities for a business‑critical B2B payments platform. This role will focus on migrating an existing Selenium test suite to Playwright, expanding scenario‑based regression coverage across payment processing, email and file parsing, and Pay Fac settlement workflows, and integrating automated testing into Git Hub Actions.

You will play a key role in establishing a more reliable, scalable approach to quality engineering, with a strong emphasis on daily automation development, end‑to‑end data validation, and AI‑assisted testing. This is an opportunity to take ownership of meaningful test coverage for a platform that processes real financial transactions.

• Develop, maintain, and enhance automated tests using Playwright across UI, API, integration, and end‑to‑end workflows.
• Support the migration from Selenium to Playwright, leveraging AI‑assisted tools such as Kiro to accelerate test creation and refactoring.
• Review and validate all AI‑generated code to ensure accuracy, maintainability, security, and appropriate test coverage.
• Maintain and optimize automated test execution in Git Hub Actions, improving reliability, speed, reporting, and overall pipeline health.
• Design scenario‑based tests with clear, predefined assertions that make failures easy to identify and diagnose.

• Execute functional, integration, end‑to‑end, and regression testing across payment processing, data parsing, settlement, and reconciliation workflows.
• Develop and maintain test cases in AIO Test, ensuring traceability to Jira stories, acceptance criteria, automated tests, and reported defects.
• Write SQL queries against PostgreSQL databases to validate data processing, enrichment, and reconciliation results.
• Build automated regression coverage for high‑volume email and file ingestion, payment APIs, and third‑party integrations.
• Identify gaps in test coverage and help prioritize testing based on business impact and integration risk.

• Use AI‑powered tools to accelerate test development, framework migration, test data generation, and failure analysis.
• Evaluate AI‑generated tests for correctness, edge cases, security considerations, coverage, and long‑term maintainability.
• Follow established AI usage, data‑handling, and code review policies, ensuring production and cardholder data are never entered into AI tools.
• Share best practices and lessons learned to improve AI‑assisted testing practices across the engineering team.

• Partner with Engineering and Dev Ops teams to support release quality gates, deployment decisions, and documented testing evidence.
• Maintain reliable test environments and repeatable test data practices using synthetic data, reusable accounts, controlled datasets, and refresh procedures.
• Track and report measurable quality metrics, including automation coverage, pass rates, defect leakage, and regression stability.
• Participate in backlog refinement, sprint planning, and release readiness reviews to identify potential risks and testing requirements early.

• 3–5 years of experience in Quality Engineering, Test Automation, or Software QA, with hands‑on experience delivering automation in Agile or Dev Ops environments.
• Practical experience with Playwright, Cypress, or Selenium for UI, API, and end‑to‑end testing.
• Ability to write SQL queries, including joins and aggregate functions, to validate data and compare actual results against expected datasets.
• Experience integrating and executing automated tests within Git Hub Actions or a comparable CI/CD pipeline.
• Experi…