Srinivas Yadam

Srinivas Yadam is a senior networking engineering leader whose career has been built at the intersection of hyperscale data center infrastructure, AI/ML-enabled networking, and large-scale system validation. At Cisco Systems, he has focused on qualifying and hardening next-generation switching and routing platforms that sit at the core of modern cloud and AI compute fabrics—where a single defect can ripple into outages, model-training delays, or multi-tenant service degradation. His work reflects a disciplined blend of architecture fluency, validation rigor, and customer-centered reliability engineering—driving measurable impact in both product success and field outcomes.

Srinivas’s technical portfolio spans end-to-end architecture and validation of advanced data center switching platforms, including Cisco’s industry-first 800G AI/ML-capable switch (Nexus 9364E-SG2-O), high-density 400G platforms (N9K-C9364D-GX2A), and programmable Nexus 9000 systems (N9336C-SE1, N9K-C9316D-GX, N9K-C93360YC-FX2, N9K-C9358GY-FXP). Working across Cisco’s proprietary SiliconOne and Cloud Scale ASIC families—alongside Broadcom-based designs—he has engineered massively scalable testbeds that mirror production environments, incorporating NVIDIA GPU clusters, high-density leaf–spine topologies, and comprehensive optics coverage. These environments are not lab abstractions; they are engineered replicas designed to de-risk real deployments at scale.

His protocol and systems expertise covers the routing and transport fundamentals required for cloud backbones and enterprise fabrics—BGP, OSPF, MPLS, L3VPN, and GRE/IPinIP—paired with security validation and programmability at modern network operations velocity. His work on IPSec Security Services for the ASR 9000 Series Virtualized Service Module expanded the platform’s capability from routing into secure encrypted transport through validation of ISAKMP, IKE/IKEv2, and cryptographic algorithm suites. He has also driven validation of modern network programmability stacks—NETCONF, RESTCONF, gNMI, model-driven telemetry—and platform containerization through Application Hosting that enables Docker-based applications directly on switch hardware.

In AI-scale networking, Srinivas has validated performance-critical features that determine whether clusters run efficiently or fail under load: Dynamic Load Balancing (DLB), Flowlet Load Balancing (FLLB), weighted ECMP, and RDMA/RoCEv2 behavior with ECN and PFC for lossless, ultra-low-latency fabrics. His observability work spans NetFlow, flow telemetry, hardware telemetry, Traffic Analytics, and mixed-mode operation across Nexus platforms—delivering real-time network visibility needed for operations and incident response at hyperscale.

Srinivas’s impact is not confined to technical correctness; it has translated into commercial and customer outcomes. He contributed to qualifying Cisco’s first 800G platform, cited as supporting $800M revenue in a single fiscal quarter. His system validation work on the N9K-C9364D-GX2A helped establish it as Cisco’s fastest-selling product in company history during a market window where competitors lacked equivalents. These platforms are deployed by strategic customers including xAI, Tesla, Oracle Cloud, AMD, and SoftBank, reflecting the trust hyperscalers and AI leaders place in the quality of the underlying network fabric.

He has also delivered foundational serviceability innovation through the Logging 2.0 initiative—re-architecting diagnostic capabilities across the Nexus portfolio via binary log conversion, intelligent throttling, and autonomous evidence collection. This work reduced tech-support collection time by ~40% and prevented outages by proactively detecting and mitigating memory leaks. As sole system test owner, he designed complex multi-generational testbeds to validate behaviors across diverse hardware platforms—creating organizational leverage well beyond a single product cycle.

In Cisco’s strategic push into hyperscale routing, Srinivas led work on the NCS 5000 Alpha/Stealth initiative, designing automation frameworks that achieved 70%+ test coverage and validating the full programmability stack for streaming telemetry and automation—supporting contracts with hyperscale operators including Microsoft, Google, Amazon, Oracle, and Facebook. In the field, he has also delivered high-urgency customer support—such as stabilizing networks for major NFL broadcasts through rapid reproduction, root cause analysis, and validated fixes—demonstrating operational credibility under pressure.

Beyond delivery, Srinivas is a knowledge leader: the point person for Logging 2.0 adoption across the business unit, delivering training, documentation, and mentorship that shaped engineering practice across teams. His work has been recognized through multiple awards for critical project delivery, infrastructure hardening, memory leak detection, and customer excellence, and he has filed a USPTO patent for an AI-powered networking debug tool, signaling thought leadership in automating root-cause discovery in complex fabrics.