Quality Assurance Engineer

Role Overview 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 • IEEE 802.1 (Bridging, VLAN, STP, MAC security, LLDP). • L2/L3 features (TCP/IP, VRRP, IGMP, IPv4/IPv6, ICMP/ICMPv6, ARP); basic IS-IS/BGP. • 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.