DescriptionGeneral: As a QA Engineer reporting to our QA Lead, you will help ensure the quality, reliability, and performance of our software products. Our engineering team practices AI-driven, spec-driven development, and our QA practice works the same way. LLMs like Claude are core working tools for us, not occasional helpers. We use them to analyze business rules, generate test cases and test data, build automated coverage, and find gaps in what we've tested. You'll work alongside developers, product managers, and architects throughout the development cycle, not at the end of it. We're looking for someone who takes real ownership of quality and brings strong testing judgment to AI-assisted work, treating AI output as a starting point to verify rather than a finished product.
Responsibilities: Use LLMs (e.g., Claude) to analyze specifications, business rules, and regulatory requirements, and translate them into structured test plans and test cases.
- Generate manual and automated tests with AI assistance, then review, correct, and refine the output so it is accurate, meaningful, and maintainable.
- Use AI to generate realistic, rules-driven test data, including edge cases, boundary conditions, and compliance scenarios.
- Use AI to analyze test coverage against specs and business rules, to identify gaps, redundancies, and untested risk areas.
- Build and refine reusable prompts, workflows, and context (e.g., spec templates, rule summaries) that make AI-assisted testing repeatable across the team.
- Apply test design techniques such as boundary value analysis, equivalence partitioning, and black-box/white-box testing, both directly and to evaluate the quality of AI-generated tests.
- Maintain automated test suites for frontend (e.g., Playwright, Cypress, Selenium) and backend/API testing (e.g., Postman, REST Assured) and keep them running reliably in CI/CD pipelines.
- Test complex business and regulatory rule logic, working with the QA Lead, developers, and architects on test harnesses and on making components more testable ("glass box").
- Develop and maintain "last mile" smoke tests and end-to-end validations that reflect real customer workflows and expectations.
- Perform database validation using SQL and support performance testing as needed.
- Participate in Root Cause Analysis and document and track defects clearly.
- Engage early in the development cycle by validating and challenging requirements and deliverables rather than rubber-stamping them and raise gaps and risks before code is written.
Required Skills and Experience: - 2-4 years of experience in software quality assurance and testing.
- Demonstrated hands-on use of LLMs in testing workflows beyond Q&A, such as generating test cases, test data, or automated tests from specs, or analyzing test coverage. Be prepared to walk us through real examples.
- Strong judgment in evaluating AI-generated output, including spotting incorrect assertions, missing scenarios, invented logic, and tests that pass without proving anything.
- Working knowledge of test design techniques and testing strategies.
- Experience with both manual and automated testing.
- Proficiency in at least one programming language (Java, Python, JavaScript/TypeScript, or C#) with the ability to read, review, debug, and modify automated test code.
- Hands-on experience with test management and defect tracking tools (e.g., Jira, X-ray).
- Experience with Git and SQL.
Preferred Skills and Experience: - Experience building prompt libraries, AI-assisted test workflows, or agentic tools (e.g., Claude Code) for QA.
- Experience with spec-driven development or testing rules engines and decisioning systems in regulated domains.
- Familiarity with cloud platforms (AWS, GCP, or Azure) and testing in cloud-native environments.
- Strong exploratory testing skills and a passion for uncovering edge cases.
- Familiarity with test automation design patterns (e.g., Page Object Model).
- Proactive in identifying quality risks and suggesting process improvements.
- A strong sense of curiosity and a mindset geared toward engaging with complex challenges and continuous learning.
Compensation: The target compensation range for this role is $110-125k, along with a comprehensive benefits package including medical, dental, vision, 401(k), and other employee programs.
