Mahendra H N

Director @NVIDIA

Bengaluru, KA, IN
MOBILE NUMBERS
+91 *********19

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WORK HISTORY

Mar 2026 — Present

Director @NVIDIA

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Bengaluru, IN

Lead end-to-end strategy and execution of OpenBMC-based platform management solutions for next-generation AI systems, owning the roadmap for GPU/accelerator-driven server platforms while leading cross-functional teams across firmware, kernel, networking, and system software. Architect scalable Redfish/IPMI management stacks for hyperscale datacenters, delivering secure boot, firmware update and telemetry frameworks. Collaborate closely with silicon vendors, ODMs, and hyperscalers to align hardware-software integration, while improving platform bring-up efficiency, system reliability, and fleet-level telemetry observability for large-scale AI training environments.

EDUCATION

1997 — 2001

Bachelor of Engineering

Bachelor's degree, Computer Science

SKILLS

People ManagementCustomer Escalation ManagementObject Oriented SystemsMpls VpnL2vpnProduct DevelopmentEmbedded SystemsRouting ProtocolsL2/L3 ProtocolsLinux KernelLinuxQosProject ManagementUnixTraffic EngineeringSnmpEthernetVirtualizationObject-Oriented Programming (Oop)Device DriversTcp/IpC

ABOUT MAHENDRA H N

Technology leader with 20+ years of experience in cloud computing, networking, and AI infrastructure software, specializing in end-to-end product development from concept to large-scale deployment. Currently leading OpenBMC-based platform management solutions for next-generation AI systems, with deep expertise across firmware, embedded Linux, and hyperscale infrastructure. Proven track record of building and scaling high-performing global engineering teams, driving innovation, and delivering complex, high-impact platforms through strong cross-functional collaboration across software, hardware, and product organizations. Experienced in managing large platform transitions, owning product sustenance and escalations, and improving system reliability, efficiency, and observability at scale. Passionate about enabling secure, resilient, and scalable infrastructure for AI workloads.

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