Senior Test Automation Engineer

2 days ago

Bengaluru, Karnataka, India beBeeAutomation Full time ₹ 15,00,000 - ₹ 20,00,000

Improve Test Automation for Intelligent Solutions

We are seeking a skilled and experienced Tooling and AI Automation Engineer to join our team. This role focuses on building internal tools, test intelligence platforms, dashboards, and AI-driven test enablement frameworks.

Key Responsibilities
  • Develop robust, scalable test automation frameworks for API, web, and mobile platforms.
  • Design, develop, and maintain internal tools that enhance automation capabilities, CI/CD integration, and test data visualization.
  • Build intelligent dashboards for real-time reporting of test results, release quality metrics, and defect analytics.
  • Develop AI/ML-based solutions to optimize test case prioritization, test suite reduction, flakiness prediction, and self-healing scripts.
  • Integrate tools and dashboards with CI pipelines (e.g., Jenkins, GitHub Actions) and test frameworks (Selenium, Playwright, etc.).
  • Collaborate with SREs, DevOps teams to ensure tools are scalable, performant, and well-adopted.
  • Create APIs, microservices, or CLI tools that support testing workflows, artifact management, and defect traceability.
Required Skills and Qualifications
  • Solid proficiency in Java/Python.
  • Strong hands-on experience in API Automation (Rest Assured) and UI Automation/Mobile Automation.
  • String experience in having built Automation Frameworks from scratch.
  • Working knowledge or experience with Mabl, TestRigor, Cursor, or any AI automation tool.
  • Strong understanding of test automation frameworks (e.g., Pytest, Playwright, Cypress, Selenium).
  • Experience integrating tools with CI/CD pipelines (Jenkins, GitHub Actions, GitLab CI).
  • Familiarity with databases (SQL, NoSQL) and working with test data at scale.
  • Experience in building REST APIs or microservices for internal use.
  • Hands-on experience in Performance Testing (for 8+ years of experience candidates).
  • Experience with GenAI or LLM integration for test case generation or failure analysis.
  • Working knowledge of AI/ML libraries like Scikit-learn, TensorFlow, or transformers for testing-centric use cases.
Benefits
  • Shape the future of intelligent test engineering.
  • Work in a culture that values automation, data-driven decisions, and innovation.

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