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 PayFac settlement workflows, and integrating automated testing into GitHub 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.

Key Responsibilities

Test Automation & Framework Development

• 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 GitHub 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.

Functional Testing & Data Validation

• 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.

AI-Assisted Quality Engineering

• 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.

Release Quality & Reporting

• Partner with Engineering and DevOps 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.

Required Qualifications

• 3–5 years of experience in Quality Engineering, Test Automation, or Software QA, with hands-on experience delivering automation in Agile or DevOps environments.
• Practical experience with Playwright, Cypress, or Selenium for UI, API, and end-to-end testing.
• Proficiency in Python and/or TypeScript, with the ability to independently develop, troubleshoot, and maintain automation code. Candidates with Java, C#, or JavaScript experience will also be considered if they have strong programming fundamentals.
• 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 GitHub Actions or a comparable CI/CD pipeline.
• Experience testing APIs, system integrations, or cloud-native applications.
• Ability to investigate test failures by reviewing application logs, identifying root causes, and troubleshooting issues before escalating them.
• Strong written communication skills, including the ability to clearly explain quality risks and their potential business impact.

Preferred Qualifications

• Experience in payments, fintech, banking, or PCI-regulated environments, particularly with settlement, funding, tokenization, or transaction processing systems.
• Experience validating high-volume data ingestion and parsing workflows involving email, EDI, batch files, or other structured data feeds.
• Familiarity with AWS services such as S3, Secrets Manager, and Step Functions, or similar cloud-based testing environments.
• Hands-on experience using AI-assisted tools for test generation, automation maintenance, refactoring, or failure analysis.
• Experience with test management platforms such as AIO Test, Xray, or Zephyr.
• Experience collaborating with distributed engineering teams or offshore QA resources.