Quality Assurance Engineer

Extreme Networks; Bengaluru; On-site; INR 900,000 - 1,500,000; Full time

Job summary

Extreme Networks is seeking a QA Engineer to join the Software Quality Assurance team as an individual contributor. You will plan, develop, automate, and execute tests spanning functional, performance, and scalability dimensions, with growing AI-driven testing focus.

You will translate feature requirements into comprehensive test strategies, build automation using Python or Golang, and integrate tests into CI/CD pipelines for repeatable validation in data center networking, routing, and security

Qualifications

• 2.5–4 years of QA/test experience.
• Bachelor's/Master's degree in CS/EE/ECE or equivalent.
• Hands-on experience in functional, system testing, and automation.
• Knowledge of data center networking concepts.
• Familiarity with AI-assisted testing tools.

Responsibilities

• Plan, develop, automate, and execute tests across functional, performance, and scalability areas.
• Translate feature requirements into test strategy and detailed plans.
• Build and maintain test automation suites in Python or Golang and integrate with CI/CD.
• Apply AI-assisted testing techniques to improve coverage and speed.
• Collaborate with development, product management, and solution engineering.
• Support data center networking, routing, and network security testing.

Skills

Networking

Test automation

AI in QA

Communication

Education

B.E./B.Tech./M.Tech./MCA

Tools

Python

Golang

Jenkins

Git

Docker

AWS

Job description

The QA Engineer is an individual contributor within the Software Quality Assurance team, working alongside Development, Product Management, and Solution Engineering to validate Extreme Networks products and solutions. The role spans test planning, test development, automation, and execution across functional, performance, and scalability dimensions, with a growing focus on applying AI-assisted techniques to accelerate the test cycle. Work closely with development engineering and product management to understand feature requirements and translate them into test strategy, test topology, and detailed test plans for data center networking, switching, routing, and network security. Build and maintain test automation suites in Python or Golang and integrate them into CI/CD pipelines for continuous, repeatable validation. Apply AI-assisted testing techniques — such as AI-generated test cases, log/defect triage, and coverage-gap analysis — to improve productivity and accelerate the test cycle.

Experience

• 2.5 to 4 years of relevant industry experience

Qualifications

• Minimum of B.E/B.Tech/M.Tech/MCA or equivalent in CS/EEE/ECE/EEE

Key Responsibilities

• BS or MS in EE/CS with 2 to 5 years of hands-on experience in functional, system test, and automation.
• Solid technical knowledge of data center networking — IP Fabric, VxLAN EVPN, and network virtualization concepts.
• Working knowledge of Ethernet, optics, and networking hardware.
• Knowledge of routing protocols (OSPF, IS-IS, BGP, Multicast) and network security fundamentals.
• Hands-on experience developing test automation using Python or Golang.
• Experience with test planning, requirement-to-testcase mapping, defect logging and tracking, and debugging.
• Exposure to AI/ML concepts or AI-assisted developer/testing tools (e.g., LLM-based assistants, GenAI copilots) applied to QA workflows.
• Strong verbal and written communication skills and the ability to collaborate cross-functionally.
• Highly motivated, self-driven, and eager to learn.

Skillset Required

Good knowledge and hands-on experience across most of the following areas:

Networking

• Network debugging tools (Wireshark, ping, traceroute) and traffic generators (Ixia/Spirent).

Test Automation

• Test scripting in Python or Golang; familiarity with automation frameworks and CI/CD (Jenkins/GitLab).
• Version control (Git) and defect/test management tools (JIRA, qTest).
• Exposure to Docker containerization and cloud environments (AWS, Azure, GCP) is a plus.

AI in the Test Cycle

• Familiarity with using AI assistants to generate/augment test cases and test data.
• Interest in AI-based log analysis, failure triage, and test-coverage gap detection.
• Understanding of prompt basics for applying GenAI tools responsibly within QA workflows.

Methodology

• Knowledge of testing methodologies, testing types, and the overall product life cycle.