Senior Test Automation Engineer (JavaScript)

Intellias; Polska; On-site; PLN 120,000 - 180,000; Full time

Job summary

Intellias is embarking on a transformative data and AI platform initiative to modernize enterprise-scale capabilities and enable real-time decision-making. The project covers AI, MLOps, data governance, and platform scalability to foster data-first operations and intelligent automation.

The role focuses on designing, developing, and maintaining automated UI, API, and E2E tests, integrating them into CI/CD, and guiding AI pods to ensure high-quality releases and robust testing coverage.

Qualifications

• 5+ years of hands-on QA and Test Automation experience.
• Strong experience with Playwright.
• UI, API and E2E automation, CI/CD, Git, test reporting and monitoring.
• Hands-on experience applying GenAI/LLMs to engineering or QA workflows.
• Experience building AI-powered tools, agents, or reusable skills around automation frameworks.
• Understanding of MCP and API-based integrations with systems such as Jira.
• Ability to evaluate and validate AI-generated testing outputs, ensuring appropriate coverage, correctness, maintainability, and adherence to QA standards

Responsibilities

• Design, develop, and maintain test automation frameworks and automated UI, API, and E2E tests.
• Integrate automated testing into CI/CD pipelines and continuously improve test coverage, tooling, and processes.
• Act as the quality engineering interface between the central QA team and teams working in AI Pods, ensuring alignment on testing approaches, standards, and release readiness.
• Ensure the quality of testing delivered by AI testing agents within AI Pods by reviewing their outputs, validating coverage and reliability, and identifying gaps requiring additional testing.
• Build AI-enabled capabilities around the test automation framework for test authoring, maintenance, execution, and failure analysis.
• Develop reusable AI skills/agents for QA workflows and integrate them with engineering and test-management systems using MCP/APIs.
• Analyse test results, troubleshoot failures, and support release readiness.
• Mentor team members and promote modern automation and AI-assisted QA practices.

Skills

QA Automation

Playwright

UI Automation

API Automation

E2E Testing

CI/CD

Git

Test Reporting

Tools

Jira

Job description

Let’s breathe life into great tech ideas! With 3,000 people globally, Intellias is a company where benchmark technological solutions are born. Join in and take your part in digitalizing the world.

Project Overview:

Join a transformative data and AI platform initiative aimed at modernizing enterprise-scale capabilities and enabling real-time decision-making. This project delivers a comprehensive roadmap covering AI, MLOps, data governance, and platform scalability, supporting a shift towards data-first operations and intelligent automation.

Requirements:

• 5+ years of hands-on QA and Test Automation experience.
• Strong experience with Playwright.
• Experience with UI, API and E2E automation, CI/CD, Git, test reporting and monitoring.
• Hands-on experience applying GenAI/LLMs to engineering or QA workflows.
• Experience building AI-powered tools, agents, or reusable skills around automation frameworks.
• Understanding of MCP and API-based integrations with systems such as Jira.
• Ability to evaluate and validate AI-generated testing outputs, ensuring appropriate coverage, correctness, maintainability, and adherence to QA standards

Responsibilities:

• Design, develop, and maintain test automation frameworks and automated UI, API, and E2E tests.
• Integrate automated testing into CI/CD pipelines and continuously improve test coverage, tooling, and processes.
• Act as the quality engineering interface between the central QA team and teams working in AI Pods, ensuring alignment on testing approaches, standards, and release readiness.
• Ensure the quality of testing delivered by AI testing agents within AI Pods by reviewing their outputs, validating coverage and reliability, and identifying gaps requiring additional testing.
• Build AI-enabled capabilities around the test automation framework for test authoring, maintenance, execution, and failure analysis.
• Develop reusable AI skills/agents for QA workflows and integrate them with engineering and test-management systems using MCP/APIs.
• Analyse test results, troubleshoot failures, and support release readiness.
• Mentor team members and promote modern automation and AI-assisted QA practices.