Senior Automation QA

We're looking for a hands-on Fullstack QA Engineer who can operate comfortably as a manual tester and build/maintain automated suites using modern agentic AI practices to deliver fast, reliable regression and release confidence.

You'll collaborate closely with Product, BA, Engineering, and stakeholders, shaping test strategy, hardening quality gates, and improving confidence in complex data-heavy workflows.

Responsibilities

Test Strategy & Planning

• Translate requirements and acceptance criteria into risk-based test plans and coverage maps across UI, API, data, reports, formulas, and integrations.
• Define and evolve a pragmatic test pyramid: unit, API, UI, smoke/sanity, regression, and UAT.
• Create coverage around spreadsheet-driven validation, report parity, and key billing / reconciliation workflows.

Manual Testing

• Create and execute test cases for new features, bug fixes, report logic, filter combinations, and change requests.
• Perform exploratory testing to uncover edge cases in data-heavy workflows, calculations, and stakeholder-facing panels.
• Validate generated outputs against canonical XLSX workbooks, including formulas, filters, totals, and rollforward variance logic.
• Log high-quality defects with clear reproduction steps, impact, evidence, screenshots, and expected vs actual results.

Test Automation (agentic-AI-first)

• Build and maintain stable, reusable automated suites for smoke and regression using modern agentic AI practices.
• Help reduce slow manual spreadsheet comparison by contributing to automated parity checks and repeatable QA flows.
• Integrate automation into CI/CD with environment tagging, parallelization, and results gating.
• Expand coverage to API, data validation, and key business workflows.

Quality Operations

• Own test data management and environment readiness.
• Track and report quality KPIs such as defect escape rate, flaky test rate, regression coverage, and cycle time to fix.
• Maintain living documentation, including test plans, suites, runbooks, and QA reports.

Collaboration & Process

• Partner with Product and BA to clarify acceptance criteria and reduce ambiguity in stakeholder requirements.
• Participate in backlog grooming, design reviews, release readiness, and stakeholder review cycles.
• Coach teammates on writing testable stories and preventing regressions.
• Continuously improve test effectiveness and reduce manual repetition.

Requirements

• 4–6+ years of QA experience testing SaaS / web applications, including significant hands-on manual testing.
• 2+ years building and maintaining automation for UI and/or API — ideally using modern agentic AI practices and/or tools like Playwright, Cypress, Selenium, or Postman.
• Strong grasp of testing methodologies: functional, regression, smoke/sanity, exploratory, risk-based testing, and test case design.
• Experience validating data-heavy applications, reports, dashboards, formulas, filters, and spreadsheet-like business logic.
• Experience with bug tracking and test management tools such as Jira, TestRail, or Zephyr.
• Comfortable with browser devtools, basic SQL, logs, and evidence-based debugging.
• Clear communicator with a strong bias for reproducibility, documentation, and practical delivery.
• Familiarity with Agile practices and fast-paced iterative delivery.

Nice to Have

• Power-user experience with modern agentic AI practices for QA: prompt design, evaluation harnesses, data sets, custom functions, CI artifacts, and reporting dashboards.
• Experience building automated parity checks for spreadsheets, reports, financial calculations, or analytics dashboards.
• API testing depth with tools such as Postman, Insomnia, or newman.
• Exposure to regulated healthcare environments, HIPAA-aware workflows, PHI handling, audit discipline, and documentation rigor.
• Basic performance, reliability, and accessibility testing experience.
• Experience testing analytics, reconciliation, billing, finance, revenue operations, or healthcare operations systems.

Project

Our client is building an analytics and reconciliation platform for a multi-facility radiology billing operation. The system surfaces scan volume, revenue, declining referrals, unbilled MRIs, and rollforward variance for finance and operations teams.

The work is focused on documentation tracking, operational analytics, billing reconciliation, and report accuracy. The current goal is MVP implementation, with several UI components already completed and a strong need to improve QA around spreadsheet-driven reporting logic.

The project operates in a healthcare-adjacent regulated environment.