NAP Network Test Automation Development Engineer

Nokia

Bengaluru

On-site

INR 2,500,000 - 4,200,000

Full time

4 days ago
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Job summary

Nokia in Bengaluru seeks a Network Test Automation Development Engineer to design and build scalable automation solutions for complex carrier-grade network products. You will combine networking expertise with modern automation, AI/ML, and CI/CD to improve quality, reliability, and delivery speed.

You will develop automated test suites using Python, Java, or Go, integrate tests into CI/CD pipelines, and apply AI/ML techniques for intelligent test generation and anomaly detection.

Qualifications

  • Bachelor degree with 8-12 years of relevant experience.
  • Hands-on experience with test automation frameworks such as Robot Framework, pytest, Selenium, and Postman.
  • Solid understanding of network protocols and architectures (TCP/IP, IP/MPLS, Routing & Switching, SDN/NFV, 4G/5G).
  • Experience with CI/CD tools and DevOps practices (Jenkins, GitLab CI, or similar).

Responsibilities

  • Design, develop, and maintain scalable automation frameworks for functional, regression, performance, and end-to-end network testing.
  • Develop automated test suites using Python, Java, or Go with frameworks such as Robot Framework, pytest, and Selenium.
  • Integrate automated tests into CI/CD pipelines to enable continuous testing and faster release cycles.
  • Apply AI/ML techniques for intelligent test case generation, anomaly detection, predictive defect analysis, and self-healing automation.
  • Analyze large volumes of test and network data to identify patterns, trends, and quality risks.
  • Develop AI-driven tools for network test data analysis, insights, and visualization.
  • Collaborate with development, product, and QA teams to ensure testability and timely defect resolution.
  • Contribute to test strategy, code reviews, design discussions, and maintain automation documentation.

Skills

Python
Java
Go
CI/CD
Debugging

Education

Bachelor's degree

Tools

Robot Framework
pytest
Selenium
Postman
Jenkins
GitLab CI
Docker
Kubernetes

Job description

As Network Test Automation Development Engineer is responsible for designing and developing scalable, intelligent test automation solutions for complex network systems. This role combines strong networking expertise with modern automation, CI/CD, and AI/ML technologies to ensure high quality, reliability, and faster delivery of carrier-grade, cloud-native network products.

HOW YOU WILL CONTRIBUTE AND WHAT YOU WILL LEARN
  • Design, develop, and maintain scalable automation frameworks for functional, regression, performance, and end-to-end network testing.
  • Develop automated test suites using Python, Java, or Go with frameworks such as Robot Framework, pytest, and Selenium.
  • Integrate automated tests into CI/CD pipelines to enable continuous testing and faster release cycles.
  • Apply AI/ML techniques for intelligent test case generation, anomaly detection, predictive defect analysis, and self-healing automation.
  • Analyze large volumes of test and network data to identify patterns, trends, and quality risks.
  • Develop AI-driven tools for network test data analysis, insights, and visualization.
  • Collaborate with development, product, and QA teams to ensure testability and timely defect resolution.
  • Contribute to test strategy, code reviews, design discussions, and maintain automation documentation.
Qualifications

You have:

  • Bachelor degree with 8-12 years of relevant experience. 7+ years of experience with strong programming skills in Python, Java, or Go for test automation and tool development.
  • Hands-on experience with test automation frameworks such as Robot Framework, pytest, Selenium, and Postman.
  • Solid understanding of network protocols and architectures (TCP/IP, IP/MPLS, Routing & Switching, SDN/NFV, 4G/5G).
  • Experience with CI/CD tools and DevOps practices (Jenkins, GitLab CI, or similar).

It would be nice if you also had:

  • Practical understanding of AI/ML concepts applied to automation or data analysis.
  • Exposure to ML libraries such as TensorFlow, PyTorch, or scikit-learn.
  • Familiarity with cloud platforms and container technologies (AWS/Azure/GCP, Docker, Kubernetes).
  • Strong analytical, problem-solving, communication, and cross-functional collaboration skills.
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