Staff QA Engineer 10348 – Data Center Networking | Python Automation|Layer2/Layer3
Extreme Networks · Hybrid
MeritLog read this listing from Extreme Networks's Lever job board and last checked it on September 12, 2026.
Source: the employer's Lever job board. Open the original listing for current details.
Job details
- Work model
- Hybrid
- Salary
- Not listed by source
- Location
- Bangalore
- Company website
- www.extremenetworks.com
Hiring context
How this role compares at Extreme Networks
Extreme Networks has 144 live roles in MeritLog’s catalog across 9 job families, and 19 of them are in data & analytics. 16 of those listings publish a pay range, a disclosure rate of 11%.
Extreme Networks concentrates this hiring in:
Counted across the job boards MeritLog tracks, at the time this page was served. Pay comparisons use only listings that publish a complete range in the same currency and period.
What the role asks for
What they're asking for
- BS or MS in EE/CS with 8+ years of hands-on experience in functional, system test, and automation, including a track record of technical leadership.Education
- Expert technical knowledge of data center networking - IP Fabric, VxLAN EVPN, and network virtualization frameworks.Skill
- Expert knowledge of Ethernet, optics, and networking hardware.Skill
- Expert knowledge of network security and routing protocols (OSPF, IS-IS, BGP, Multicast).Skill
- Proven experience architecting large-scale system test topologies and automation frameworks using Python or Golang.Skill
- Demonstrated leadership in introducing AI/ML or GenAI into QA - building or adopting AI-assisted testing, triage, or analytics capabilities at team or org scale.Skill
- Deep experience in performance, scale, and convergence testing and in analyzing and improving system-level performance.Skill
- Ability to author and publish solution validation documents, reference architectures, and test reports.Skill
- Excellent communication skills and the ability to influence at all levels of the organization.Skill
- Highly motivated, self-driven, and able to lead cross-functionally toward challenging goals.Skill
- IEEE 802.1 (Bridging, VLAN, STP, MAC security, LLDP, AVB) and advanced L2/L3 (TCP/IP, VRRP, IGMP, IPv4/IPv6, ICMP/ICMPv6, ARP, IS-IS, BGP, Multicast).Skill
- Data center fabric design, network virtualization (VMware NSX, OpenStack), and network security architecture.Skill
- Traffic generators (Ixia/Spirent) and advanced debugging (Wireshark, packet analysis).Skill
- Architecting automation frameworks in Python/Golang and defining CI/CD strategy (Jenkins/GitLab).Skill
- Automation for end-to-end solution validation, integrated for seamless, continuous testing.Skill
- Docker containerization, clustering, and cloud environments (AWS, Azure, GCP).Skill
- Strategy and rollout of AI-assisted test-case generation, intelligent test selection and prioritization, and self-healing automation.Skill
- AI/ML-based log analysis, automated failure triage, anomaly detection, and predictive coverage/quality analytics.Skill
- Responsible-AI practices and governance for applying GenAI tooling within QA workflows.Skill
- Test strategy ownership, mentoring, and setting engineering standards.Skill
- Deep knowledge of testing methodologies, testing types, and the full product life cycle.Skill
Parsed by MeritLog from the employer’s own posting. The full description follows below.
Job description
Job Description: Qualifications and Requirements Experience: 8-13+ Years • BS or MS in EE/CS with 8+ years of hands-on experience in functional, system test, and automation, including a track record of technical leadership. • Expert technical knowledge of data center networking - IP Fabric, VxLAN EVPN, and network virtualization frameworks. • Expert knowledge of Ethernet, optics, and networking hardware. • Expert knowledge of network security and routing protocols (OSPF, IS-IS, BGP, Multicast). • Proven experience architecting large-scale system test topologies and automation frameworks using Python or Golang. • Demonstrated leadership in introducing AI/ML or GenAI into QA - building or adopting AI-assisted testing, triage, or analytics capabilities at team or org scale. • Deep experience in performance, scale, and convergence testing and in analyzing and improving system-level performance. • Ability to author and publish solution validation documents, reference architectures, and test reports. • Excellent communication skills and the ability to influence at all levels of the organization. • Highly motivated, self-driven, and able to lead cross-functionally toward challenging goals. Skillset Required Deep expertise and demonstrated leadership across most of the following areas: Networking • IEEE 802.1 (Bridging, VLAN, STP, MAC security, LLDP, AVB) and advanced L2/L3 (TCP/IP, VRRP, IGMP, IPv4/IPv6, ICMP/ICMPv6, ARP, IS-IS, BGP, Multicast). • Data center fabric design, network virtualization (VMware NSX, OpenStack), and network security architecture. • Traffic generators (Ixia/Spirent) and advanced debugging (Wireshark, packet analysis). Test Automation • Architecting automation frameworks in Python/Golang and defining CI/CD strategy (Jenkins/GitLab). • Automation for end-to-end solution validation, integrated for seamless, continuous testing. • Docker containerization, clustering, and cloud environments (AWS, Azure, GCP). AI in the Test Cycle • Strategy and rollout of AI-assisted test-case generation, intelligent test selection and prioritization, and self-healing automation. • AI/ML-based log analysis, automated failure triage, anomaly detection, and predictive coverage/quality analytics. • Responsible-AI practices and governance for applying GenAI tooling within QA workflows. Leadership & Methodology • Test strategy ownership, mentoring, and setting engineering standards. • Deep knowledge of testing methodologies, testing types, and the full product life cycle.
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