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AI-Enabled QA Engineer
Important: This role is open to candidates based in LATAM, Africa, and Eastern Europe. Please note that as this role supports U.S.-based clients, candidates must be available to work during U.S. business hours aligned with the client’s time zone.
The AI-Enabled QA Engineer will test the tools supporting acquisitions, financial analysis, approval workflows, and marketing operations, ensuring they are accurate and production-ready.
This role will write automated checks, test edge cases, validate AI-generated outputs against source data, and help define what “production-ready” means for the organization. The AI-Enabled QA Engineer will work closely with the engineer, product manager, M&A and marketing leads, and the Head of IT.
Write actionable bug reports that engineers can use without requiring additional meetings.
Use SQL to independently verify data through joins, aggregation, and record-level investigation.
Validate status codes, payload structures, authentication failures, and behavior on repeated identical requests.
Evaluate AI-generated output using a fixed set of examples.
Verify target-analysis summaries against source financials so every number in an AI-generated summary is traceable to a document.
Test the diligence data room against cases including missing documents, duplicate uploads, and rooms that appear complete but are not.
Write test cases for AI-generated outputs that every change must continue to pass.
Check generated brand assets across eight to ten new brands.
Ensure assets do not contain branding belonging to another brand.
Develop the production-ready checklist with the Product Manager and Head of IT.
Apply the production-ready checklist to the first tool.
3+ years of QA experience across both manual and automated testing.
Experience creating a definition of done that an organization adopted is a plus.
Hands-on ability to use Playwright, Cypress, or Selenium for interface testing.
Performance testing, synthetic test-data generation, accessibility checks, and Power Platform testing are additional skills that are beneficial but not required.
Within the first 90 days:
The diligence data room is tested against realistic edge cases.
A production-ready checklist is written with the Product Manager and Head of IT and applied to the first tool.
The AI-Enabled QA Engineer will work directly with the engineer, Product Manager, M&A and marketing leads, and Head of IT to establish testing standards for tools supporting acquisitions, financial analysis, approval workflows, and brand assets. The role combines manual and automated QA, with half of the work focused on building checks that can run automatically.
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