Staff QA Engineer 10348 – Data Center Networking | Python Automation|Layer2/Layer3
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Before you apply
LocationBangalore
Work modehybrid
Typefull-time
SeniorityLead
Experience8–13 yrs
DepartmentProducts, Engineering
Company size1,001–5,000 people
PostedJul 28, 2026 · 3mo ago
Verified live2h ago
May no longer be actively hiring
Posted by the company on Jul 28, 202651% of this company's open roles have been listed for 90+ days
At a glanceSummarised by Seekless from the posting.
BS or MS in EE/CS
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
Deep expertise and demonstrated leadership across most of the following areas: IEEE 802.1, Data center fabric design, network virtualization, network security architecture, Traffic generators, Debugging
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)
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
Test strategy ownership, mentoring, and setting engineering standards
Deep knowledge of testing methodologies, testing types, and the full product life cycle
Skills
Python
Golang
Ixia
Spirent
Wireshark
Jenkins
GitLab
Docker
AWS
Azure
GCP
VMware NSX
OpenStack
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.