Note: The job is a remote job and is open to candidates in USA. Amplifire is an adaptive eLearning platform built from discoveries in brain science that helps organizations improve learning outcomes. The Senior QA Automation Engineer will build and maintain automated regression suites, contribute to test strategy, perform manual and exploratory testing, and partner with engineering and product teams to ensure reliable, high-quality releases. The role also applies AI-assisted testing pragmatically within a regulated environment where auditability, correctness, and reliability are essential.
Responsibilities
- Build and maintain automated regression suites using Cypress and Playwright
- Own test planning and execution for complex features and workflows
- Perform manual and exploratory testing where automation alone is not sufficient
- Partner with engineering and product to identify risk early and embed quality throughout the development process
- Maintain high-quality test cases, documentation, and defect reporting
- Track defects in Jira and contribute to quality metrics
- Conduct root cause analysis on production issues and help identify prevention strategies
- Use AI tools to support test design, analysis, automation, and coverage improvement
- Contribute to AI-assisted testing workflows that help reduce repetitive work and improve release confidence
- Help evaluate AI-driven features for quality, reliability, and consistency
- Follow and contribute to evolving best practices for responsible AI-assisted QA workflows
- Use modern AI tools pragmatically while validating outputs and maintaining strong QA standards
Skills
- 5+ years of experience in Quality Assurance, including designing and maintaining automated test frameworks in production environments
- 3+ years of experience with Cypress or Playwright using Typescript or JavaScript
- Strong QA fundamentals, including test coverage strategy, risk assessment, defect writing, and regression planning / execution
- Experience owning QA work for complex features or systems with minimal oversight
- Experience using AI tools to support testing workflows, such as generating test cases, analyzing results, improving coverage, or accelerating repetitive QA work
- Exposure to testing AI/LLM-driven features or interest in developing stronger evaluation practices for AI-assisted functionality
- Familiarity with modern AI development tools and workflows, such as Copilot, Claude Code, or similar
- Comfortable working across a modern web stack (e.g., React, TypeScript, Java, Python) and combining automation, manual, and exploratory testing for full system coverage
- Strong debugging, problem-solving, and communication skills, with the ability to influence quality practices through clear thinking, execution, and collaboration
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