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QA Software Engineer 10350 – L2/L3 Networking | Python Automation | VxLAN EVPN

Extremenetworks
CompanyExtremenetworks
CategoryUncategorised
LocationBangalore
RemoteHybrid
EmploymentFull-time
LevelNot stated
SalaryNot stated by the employer
Posted28 Jul 2026
Last verified30 Jul 2026
SourceEmployer career page (lever)
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Description
Qualifications and Requirements:   Experience: 2-5 Years •    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
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