Middle General QA Engineer (with AI experience)

We are looking for a Middle General QA Engineer to join a configuration-driven product platform. Much of what we ship is generated — configuration from designs, styling from design tokens, and code produced by agents under developer review — so your core contribution is verifying that output against intent before it reaches users, using manual, automated and AI-assisted testing.

About the project

A configurable platform powering around 15 live affiliate products. Each product is assembled from three layers: application code, styling generated from brand variables and design tokens, and configuration that wires up pages, questions, checklists, dashboards, coach rules, personas and content rotations across many Admin file types. Figma is the visual CMS and source of truth for designs, content, display conditions and metadata, and releases move through four environments on a dev → test → stage → production path. Internal tooling includes an Admin MCP server that lets agents read and write configuration, a read-only data connector over AWS, and Figma integration.

Responsibilities

• Analyze requirements, designs and BA specifications to identify test scenarios and ensure coverage.
• Create and maintain manual and automated test cases, checklists and regression suites.
• Use AI-assisted, automated and manual testing techniques across the four-environment release path, selecting the most effective approach for each testing scenario. 
• Verify generated configuration, styling and code against the design, the specification and the reference product before release.
• Run blind-test and diff checks — generate from the design alone, diff against the known-good export, then verify every field and string character-exact.
• Use agentic browser testing and AI tooling to check functionality, styling and configuration together, and to accelerate test design and repetitive tasks.
• Build validation into the configuration and styling pipelines so checks run inside the pipeline rather than after it.
• Report, track and clarify defects with the development team and BA, including review and triage sessions.
• Manage test planning, QA reports and release readiness for the products you cover.
• Document rules, worked examples, checklists and runbooks that both people and agents can reuse.
• Communicate effectively with the client and the team about progress and project quality.

Requirements

• 2,5+ years of experience in Quality Assurance, covering web, backend, and mobile applications.
• Hands-on experience in test automation using Playwright (test creation, execution, and maintenance).
• Knowledge of JavaScript/TypeScript.
• Hands-on experience with API testing.
• Practical experience with AI-powered tools to enhance QA processes, including:
  • Accelerating test design and scenario generation;
  • Supporting exploratory and regression testing;
  • Detecting gaps, anomalies, and coverage issues.
• Practical experience with agentic browser testing (e.g. Playwright MCP, or driving a live system with an AI agent) to validate functionality, styling and configuration together.
• Experience reading Figma as a specification source – extracting design intent, content, and display conditions to build or verify test scenarios and configuration.
• Confidence verifying work you did not write: reading a diff and checking output against a specification or design.
• Ability to create clear and structured test documentation that both people and agents can act on.
• Willingness to connect your AI assistant to project systems via MCP and work in a shared-context setup.
• Awareness of safe data handling when using AI agents against live-like environments – avoiding exposure of real user data to AI tooling where synthetic/anonymized alternatives exist.
• Upper-Intermediate or higher spoken and written English.
• Ability to travel internationally for individual client meetings.
• A plus: prior experience building or configuring your own AI-assisted testing tooling (e.g. custom prompts/scripts for test generation), contributing to a shared prompt/playbook library, or familiarity with LLM-as-judge style evaluation for AI-generated output.

Soft skills

• Strong analytical skills and attention to details — on this platform, character-exact matters.
• Constructively skeptical: assumes fluent, confident output can still be wrong, and checks.
• Proactive and hard-working, with excellent communication skills.
• High sense of responsibility and ownership.
• Adaptable to a fast-moving environment with evolving requirements.
• Eager to learn new techniques, incorporate AI-driven testing into daily QA workflows, and share what they learn.

We offer

• Competitive compensation based on your skills, experience, and performance.
• Enterprise AI tooling, your choice of model, and time to experiment with it.
• A shared prompt and playbook library, with peer-led learning in the flow of work.
• 20 working days of annual paid vacation and 5 days of sick leave.
• 3 additional days off for special occasions.
• Experienced colleagues with 95% of middle and senior engineers.
• Possibility to work from anywhere in the world.
• Exciting projects involving the newest technologies.
• Accounting as a service.
• Flexible working approach.