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. Our primary clients are banks, life insurers, and pension providers, for whom compliance and absolute data accuracy are critical. 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 Figma specifications to build comprehensive test scenarios (including conditional content and boundary values), and verify generated configuration, styling, and functionality against them prior to release. * 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. * Triage and validate AI-generated output to ensure results accurately reflect intended business logic and design specifications. * 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. * Perform testing on real mobile devices and validate key customer journeys across mobile experiences. * Document rules, worked examples, checklists, and runbooks that both people and agents can reuse. * Continuously improve AI-assisted testing workflows, prompts, and validation processes based on lessons learned during testing activities. * 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, browser developer tools, JSON payloads, and tracing data flow to UI rendering. * 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 similar AI-assisted approaches). * 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 evaluate AI-generated output and distinguish genuine product defects from incorrect AI conclusions. * 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 practices when using AI tools and agents in testing environments. * 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. * Evidence-driven and constructively skeptical, with a habit of validating assumptions through observation and verification rather than relying on intuition or AI-generated output. * 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.
