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hirly last saw it live on 2 September 2026. See similar open roles below, or browse all Software Engineer jobs in Bengaluru.

Extremenetworks

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

Bangalore

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hirly's read of this role

Role family
Engineering
Seniority
Mid level
Country
IN
Work mode
On-site / unstated
First seen by hirly
2 Sept 2026

Derived automatically from the posting.

the posting

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
Original posting on Extremenetworks's site ↗

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