Quality Assurance Engineer

About Boost Payment Solutions Boost Payment Solutions is transforming B2B payments through secure, cloud-native platforms for payment processing, payment facilitation, settlement, and enterprise payment workflows. Our technology moves mission-critical financial transactions where reliability, accuracy, and security are non-negotiable. About the Role You will join a Quality Engineering function that is being rebuilt, not maintained. We are migrating an existing Selenium suite to Playwright, standing up scenario-first regression coverage across Gen-3 payment processing, email and file parsing, and PayFac settlement, and wiring it into GitHub Actions so quality signal appears on every pull request. You will write automation daily, use AI tooling to accelerate test creation and migration, and own real coverage on a platform that processes live money. If you are looking for a mature suite to maintain, this is not that role. If you want to build one, it is. Why this role matters You own measurable regression coverage on mission-critical B2B payment flows — not a slice of someone else's suite. You work across the full stack of quality signal: UI, API, database validation, and CI pipeline health. You use AI tooling in production practice, not as an experiment — with review standards that keep it trustworthy. What You'll Do Automation & Framework Contribution Build and maintain automated tests in our Playwright framework across UI, API, and end-to-end suites. Contribute to the Selenium-to-Playwright migration using AI-assisted tooling (Kiro), reviewing all generated output before merge. Keep tests running in GitHub Actions — improving stability, execution speed, and reporting while retiring flaky and low-value tests. Follow the scenario-first design standard: one scenario, one fixed assertion set, so a failure names itself without an SME. Test Execution, Coverage & Traceability Execute functional, integration, end-to-end, and regression testing across payment processing, parsing, and settlement workflows. Write and maintain test cases in AIO Test with traceability to Jira stories, acceptance criteria, automation, and defects. Validate data end to end — write SQL against Postgres schemas to confirm parsing, enrichment, and reconciliation results, not just UI state. Build regression coverage for high-volume email and file ingestion, payment APIs, and third-party integrations. AI-Assisted Quality Engineering Use AI tooling to generate, refactor, and maintain automated tests, test data scenarios, and failure analysis. Review every AI-generated test for correctness, coverage, edge cases, security, and maintainability before it lands. Operate within Boost's AI usage, data-handling, and code review standards — no production or cardholder data in AI tooling. Share what works and what doesn't, so practice improves for the whole team rather than one engineer. Release Quality, Environments & Reporting Support release quality gates and promotion decisions with Engineering and DevOps, including evidence capture for each gate. Apply repeatable test data and environment readiness practices — synthetic data, reusable accounts, controlled datasets, and refresh procedures. Report quality metrics in binary terms: automation coverage, pass rate, defect leakage, and regression health — with numerator and denominator, not narrative. Join backlog refinement, sprint planning, and release readiness reviews to surface coverage gaps and integration risk early. What You Bring Required 3–5 years in Quality Engineering, Test Automation, or Software QA, with hands-on automation delivery in Agile or DevOps environments. Working experience with Playwright, Cypress, or Selenium across UI, API, and end-to-end automation. Proficiency in Python and/or TypeScript sufficient to write and maintain automation code independently. (Java, C#, or JavaScript backgrounds considered where the fundamentals are strong.) Ability to write SQL for data validation — joins, aggregates, and result comparison against expected datasets. Experience running automated tests in GitHub Actions or a comparable CI/CD pipeline. Experience testing APIs, integrations, or cloud-native applications, and comfort reading logs to diagnose a failure before escalating it. Clear written communication — able to state a quality risk in terms of business impact. Preferred Payments, fintech, banking, or PCI-regulated experience — settlement, funding, tokenization, or transaction platforms. High-volume data ingestion or parsing validation (email, EDI, batch file, or similar structured feeds). AWS experience — S3, Secrets Manager, Step Functions, or equivalent cloud-native testing exposure. Hands-on use of AI-assisted tools for test creation, maintenance, or failure analysis. Test management tooling (AIO Test, Xray, Zephyr), and experience working with distributed or offshore teams. What we use Automation Playwright (migrating from Selenium) · Python · TypeScript API & data REST Assured / Postman · SQL against Postgres · S3 · Snowflake (in progress) CI/CD GitHub Actions — PR smoke gate, nightly full regression, post-deploy production smoke Test management AIO Test (Jira-native) · Jira · Confluence for strategy and evidence AI tooling Kiro for spec-driven test generation and Selenium-to-Playwright migration Cloud AWS — S3, Secrets Manager, Step Functions What Success Looks Like in Your First Year

Area Expected impact Coverage Reliable automated coverage across the critical workflows, APIs, and integrations you own. Speed Tests run in CI on every PR and nightly Traceability Your test cases map cleanly to Jira stories, automation, and defects. AI leverage A meaningful share of your test creation and maintenance is AI-accelerated and reviewed to standard. Our Hiring Process Recruiter conversation — role, background, and logistics. Hiring manager screen — your hands-on automation experience, in specifics. Practical exercise — you will review an existing automated test, identify what is wrong with it, and propose improvements. We care how you think about test design, not whether you memorized syntax. Team interview — collaboration with Engineering, Product, and DevOps. Why Boost Direct impact on platform reliability, release confidence, and customer experience on live payment rails. A quality function with executive sponsorship and a funded roadmap — not an afterthought. Real exposure to cloud-native platforms, AI-enabled engineering practice, and modern delivery models. Room to grow into senior quality engineering work as the function scales. Compensation & equal opportunity Base salary range: $140,000– $150,000, plus bonus and benefits. Final offer reflects experience, skills, and location. Boost Payment Solutions is an equal opportunity employer. We consider all qualified applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other protected characteristic.