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As a technology leader across mobile, fixed and cloud networks, our solutions enable a more productive, sustainable and inclusive world.

The Network Test Automation Engineering Manager leads and drives the test automation strategy for complex network products and end-to-end solutions. This role combines technical depth, people leadership, and strategic ownership to deliver scalable automation frameworks, AI/ML-driven testing solutions, and continuous quality improvements across carrier-grade, cloud-native network platforms.

  • Lead, mentor, and manage a team of test automation engineers, fostering a culture of innovation, collaboration, and continuous improvement.
  • Own team performance management, including goal setting, feedback, coaching, and career development.
  • Define and execute the test automation strategy and roadmap aligned with product and business objectives.
  • Architect and govern scalable, robust automation frameworks and testing tools for network solutions.
  • Oversee development and execution of automated tests for functional, performance, scalability, and regression testing.
  • Drive integration of test automation into CI/CD pipelines and DevOps workflows.
  • Lead adoption of AI/ML techniques for intelligent testing, anomaly detection, predictive defect analysis, and self-healing automation.
  • Monitor quality metrics, report automation progress and defect trends, and ensure compliance with quality standards.

You Have:

  • 10+ years of experience, including 3-5 years in a technical leadership or people management role within test automation or quality engineering.
  • Strong expertise in network technologies (IP/MPLS, SDN/NFV, 4G/5G, LTE, Ethernet, Optical and Fixed Networks).
  • Proven experience designing and scaling test automation frameworks using Python, Java, or Go with tools such as Robot Framework, Selenium, and pytest.
  • Solid understanding of CI/CD pipelines and DevOps practices.
  • Hands-on experience with cloud and container platforms (AWS, Azure, GCP, Docker, Kubernetes).
  • Practical experience or strong understanding of AI/ML applications in testing, data analysis, or network operations.
  • Strong leadership, communication, stakeholder management, and decision-making skills.
  • Excellent analytical, problem-solving, and multi-project management capabilities.
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