QA Engineer: AI-Assisted Testing

3 to 7 years in software quality assurance for web or SaaS applications, with deep experience in exploratory and manual testing of complex, data-heavy systems.

AI Fluency

• ·You use AI assistants in your testing every day and can give concrete examples: generating test ideas and edge cases, building test data, writing SQL or log queries, summarizing logs or diffs, reproducing bugs, and drafting clear reports.
• Skill at prompting and giving context, such as feeding in the ticket, the diff, and the acceptance criteria to get useful output instead of generic answers.
• Healthy skepticism. You verify what AI tells you, recognize when it is confidently wrong, and never let it replace your own judgment about risk.
• An understanding of how to test systems that don't always give the same answer, such as AI features, by using repeated trials, sample sets, and "is this answer right?" checks rather than exact matches.
• Careful handling of data. You use synthetic or masked data with AI tools and never paste customer or court data into unapproved services.

• Experience writing or maintaining automated tests (for example Playwright, Selenium, or API test scripts), including building them with AI and reviewing and fixing what it produces.
• Experience testing AI or LLM features, such as checking classification accuracy, spotting hallucinations, or testing for prompt injection.
• SQL skills for checking data in PostgreSQL.
• Experience testing APIs directly with tools like Postman, curl, or Bruno, and an understanding of HTTP, REST, and JSON.
• Experience with web security testing, including authentication and sessions, roles and permissions, OAuth2/SAML, CSRF, and XSS.
• Experience using AI browser tools (for example Playwright MCP or browser agents) to speed up exploratory testing.
• Experience testing integrations with third-party systems, email-driven workflows, or browser automation against external sites.
• Experience with accessibility testing (WCAG 2.2 AA).
• Knowledge of the legal domain, especially court e-filing, docketing, or legal document management.
• ISTQB or a similar QA certification.
• An understanding of or experience with the Lean Startup approach.

Why QA Engineers Like It Here

• Modern Tooling: Company-provided AI tools, with clear guidelines for using them safely.
• Real Impact: You'll shape how we test in an AI-assisted team, not follow a fixed script.
• AI in Production: Hands-on work testing real AI features used by law firms every day.
• · Comfort with the command line
• and reading logs. Some experience with Docker or Kubernetes (such as port-forwarding or checking pod logs) is a plus.
• · Experience with defect tracking and test management in Jira.
• Analytical Mindset: Sharp attention to detail, curiosity, and a methodical approach to breaking software and finding root causes.
• Communication Excellence: Strong written and verbal communication for bug reports, test notes, and status updates. Your reports are precise enough that another person, or an AI agent, can pick them up and act.
• Ownership: When something seems "untestable," you find a way, whether that's a query, a log search, a simulator, or a question to the right engineer, rather than skipping it.