Sr Network Test Engineer — Data Center Fabrics

• →Design, build, and execute test plans for functional/feature validation, customer use cases, and proof-of-concept engagements on data center switching platforms.
• →Design, develop, and execute comprehensive test plans to validate Junos/Sonic functionality on Broadcom-based switching platforms.
• →Replicate customer network architectures in the lab, including multi-stage IP Clos fabrics (3-stage, 5-stage, and 7-stage spine-leaf designs).
• →Perform functional, interoperability, scale, and convergence testing of BGP-based underlays and EVPN-VXLAN overlays.
• →Test AI/ML data center fabric use cases — RoCEv2 traffic profiles, lossless Ethernet behavior (PFC/ECN/DCQCN tuning), congestion management, and load-balancing efficiency across GPU back-end fabrics.
• →Validate IPv4 and IPv6 unicast/multicast forwarding, dual-stack designs, and IPv6-only fabric use cases.
• →Configure and troubleshoot routing and overlay protocols: BGP (eBGP/iBGP underlay designs, route reflectors, route policies, communities, and multipath); EVPN route types; VXLAN bridging and routing (CRB/ERB); multihoming (ESI-LAG); and DCI scenarios.
• →Use traffic generators (e.g., Ixia/Keysight, Spirent) to build traffic profiles, measure throughput, latency, packet loss, and convergence times.
• →Identify, isolate, and document software defects; work with development teams to reproduce issues and verify fixes.
• →Author clear, detailed test plans, test reports, and PoC summary documents for internal stakeholders and customers.
• →Automate repetitive test workflows using Python, pytest, Ansible, or similar frameworks where applicable.
• →Present test findings and demonstrations to customers during PoC reviews and technical deep-dives.
• →Test and verify SAI (Switch Abstraction Interface) integration and ASIC driver behavior
• →Validate optical modules across various speeds, breakout configurations, and transceiver management protocols.
• →Contributions to SONiC or other open-source networking projects (highly valued)

• Bachelor’s or Master’s degree in Electronics, Computer Science, or a related field 7 - 10 years of experience in network software/testing/engineering/TAC/escalation role.
• Strong understanding of IPCLOS fabric architecture, AI/ML fabric, BGP, EVPN-VXLAN, and IPv6 networking protocols.
• A testing duty for AI/ML fabric use cases, including RoCEv2 traffic profiles and PFC/ECN/DCQCN tuning validation.
• Strong hands-on CLI experience with at least one major data center NOS (e.g., Junos, NX-OS, EOS, SONiC).
• Strong hands-on traffic generation and analysis tools (Ixia/Keysight IxNetwork, Spirent TestCenter, or open-source equivalents).
• Strong troubleshooting methodology — able to isolate issues across the control plane, data plane, and optics/physical layer.
• Strong analytical, debugging, and documentation skills. Excellent written and verbal communication skills, ability to produce customer-facing test reports, and presentation skills.
• Hands-on experience with SONiC NOS and SAI-based architectures  (preferred)
• Experience with traffic generators like Spirent or IxNetwork
• Familiarity with Broadcom SDKs such as SDKLT or OpenNSL (preferred)
• Solid grasp of SONiC architecture: SAI, FRR, Redis DB, Docker, Minigraph (preferred)
• Exposure to telemetry, gNMI, OpenConfig, and YANG/Netconf/REST API testing
• Proficient with Git, Jenkins, Docker, and lab-based testbed environments

• Experience running customer PoC labs or certification/qualification/functional testing for a network equipment vendor, hyperscaler, or large enterprise.
• Hands-on experience with AI fabric benchmarking and validation tools (e.g., NCCL tests, perftest/ib_write_bw for RoCE, collective communication workload simulation)
• Familiarity with emerging standards such as Ultra Ethernet (UEC); exposure to InfiniBand is a plus.
• Familiarity with 100G/400G/800G optics (LR4, CWDM4, DR4, FR4), transceiver qualification, and high-density fixed/modular platforms.
• Scripting and automation experience — Python, pytest, Robot Framework, Ansible, or REST/NETCONF/gNMI-based automation.
• Exposure to telemetry and monitoring (gNMI/OpenConfig, SNMP, sFlow/IPFIX).
• Knowledge of GPU cluster back-end network designs (rail-optimized and fat-tree Clos topologies), RDMA over Converged Ethernet (RoCEv2), lossless Ethernet mechanisms (PFC, ECN, DCQCN), congestion control and advanced load balancing (dynamic/adaptive load balancing and flowlet switching), and 400G/800G connectivity for AI/ML training and inference workloads
• Relevant certifications such as JNCIP-DC/JNCIE-DC, CCNP/CCIE Data Center, or equivalent.

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