Sr. Software Engineer

Supermicro•San Jose, CA

About The Position

We are looking for an experienced Senior Software Engineer to architect and lead development of switch agent and network management software for large-scale AI and data center fabrics. In this role, you will own the technical direction of software that runs on network switches and the services that provision, monitor, and troubleshoot them at cluster scale. The roadmap extends deeper into switch silicon and telemetry, and into making the resulting data and logs directly consumable by AI agents. The ideal candidate pairs deep systems and networking expertise with the judgment to set technical direction across teams. You will establish yourself as a specialist in AI networking products built on Supermicro switches and NVIDIA/AMD GPU servers, partner closely with Product Management and customers to shape the roadmap, and mentor engineers as the platform scales.

Requirements

Bachelor's or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field (or equivalent experience).
8+ years of relevant industry experience, including technical leadership across complex systems.
Deep knowledge of L2/L3 networking protocols and management protocols, with experience on network operating systems such as SONiC and switching platforms such as Broadcom or Marvell.
Proven systems software expertise with proficiency in Go and Python (C/C++ a plus), and comfort debugging across firmware, driver, OS, and application layers.
Demonstrated experience in high-performance networking and system-level debugging, including packet drops, retransmissions, congestion, QoS, ordering, telemetry, and buffer management.
Hands-on experience with switch ASICs, ideally Broadcom (BCM), and the abstraction or SDK layers above them such as SAI, syncd, or vendor SDKs, including ASIC counters, resource tables, and silicon-level debugging.
Strong background in network telemetry, including model-driven and streaming interfaces such as gNMI, gNOI, or OpenConfig, and export mechanisms such as sFlow, IPFIX, or in-band telemetry, along with the pipelines that collect, store, and analyze that data at scale.
Experience designing datasets for machine consumption; familiarity with AI/LLM agent integration is a strong advantage.
Strong experience with Linux/Unix operating systems, containers, and REST API design.
Excellent interpersonal skills, with the ability to clearly explain complex topics to engineers, Product Managers, and customers, and communicate effectively; strong ability to self-manage.
Results driven and comfortable multitasking in a dynamic environment with shifting priorities and changing requirements.

Nice To Haves

Docker
Ansible
Git
Redis
Prometheus/Grafana
AI agent frameworks
RDMA
RoCE
VXLAN
GPU cluster fabrics
network controller software

Responsibilities

Architect, design, and develop innovative, scalable, and high-performance software solutions for AI networking products spanning Supermicro switches and NVIDIA/AMD GPU server fabrics.
Own end-to-end technical design of on-switch agent software and the management services it integrates with, from APIs and data models through deployment, upgrade, and lifecycle management.
Lead deep technical engagements with customers, involving design, coding, bring-up, performance tuning, failure analysis, and production hardening.
Drive performance, reliability, and debuggability improvements across AI clusters, including telemetry, metrics, and automated diagnostics.
Architect ASIC-level and platform telemetry pipelines, spanning hardware counters, buffer and queue statistics, and drop and error reporting, from switch silicon through to fabric-wide analytics.
Define how collected telemetry, counters, logs, and events are structured, labeled, and enriched so they can be consumed directly by AI agents and automated diagnostic workflows.
Partner with Product Managers, program management, and cross-functional teams to translate customer and market requirements into executable technical roadmaps.
Set and uphold engineering standards across design and code review, test strategy, documentation, and operational readiness for released software.
Mentor engineers and grow the team's depth in network operating systems, switch software, and fabric-scale diagnostics.
Continuously evaluate new technologies and AI-assisted approaches to improve software development efficiency, diagnostics, and operational workflows.