Senior Platform Engineer — AI/ML & GPU Compute

020 Cisco Systems, Inc.; San Jose (CA); On-site; USD 168,000 - 245,000; Full time

Job summary

Cisco Systems, Inc. is seeking a Senior Platform Software Engineer for the Platform Engineering team to own architecture and operation of the control-plane and scheduling systems for multi-cluster GPU infrastructure.

You’ll shape scalable Kubernetes-based solutions, APIs, and workflows that manage tenant quotas and optimize training and inference workloads. The role combines deep systems software engineering with API design and operational leadership, mentoring engineers and driving reliability

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience.
• 8+ years of software engineering experience building, architecting, or extending Kubernetes-based platforms or large-scale distributed systems, including technical leadership experience.
• Strong software development proficiency in Go or Python, with a proven track record architecting platform control-plane services, custom APIs, Kubernetes Controllers, Operators, or CRDs.
• Hands-on experience building, architecting, or operating batch and accelerator schedulers (e.g., Kueue, Volcano, Slurm, or custom scheduler plugins) for GPU or AI/ML workloads.
• Deep experience with GPU scheduling, multi-tenant GPU infrastructure, or managing workloads on accelerated compute platforms.
• Proven track record designing for reliability and operational excellence with Infrastructure as Code (e.g., Terraform), GitOps, CI/CD, and cloud-native observability tools (e.g., Splunk, Prometheus, Grafana).

Responsibilities

• Architect and develop platform control-plane services, APIs, and controllers to manage multi-cluster lifecycle, tenant project onboarding, and GPU quota enforcement across shared and dedicated pools.
• Own the technical architecture for GPU capacity scheduling and allocation — including fractional GPU allocation, multi-tenant isolation, and workload-aware scheduling logic that accounts for training (checkpointing, preemption tolerance) vs. inference (latency sensitivity, multi-node placement) differences.
• Drive the design and development of automated capacity-intake, demand-classification, and request-routing tooling that routes workloads to the right cluster and compute pool.
• Architect automated remediation tooling that detects node and workload failures, triggers automated remediation, and optimizes system-wide performance for training and inference workloads.
• Design, build, and scale reliable Kubernetes-based platforms (OpenShift or upstream Kubernetes) as the foundation of the AI Compute Platform.
• Lead design reviews and set technical standards for platform services, Kubernetes Operators, Controllers, CRDs, and automation built with Go and Python.
• Mentor engineers across the team, raising the bar on cloud-native software engineering practices and platform reliability.
• Drive Infrastructure as Code, GitOps, and CI/CD automation for the platform; participate in on-call rotation, incident response, and postmortem reviews.

Skills

Go

Python

Kubernetes

Distributed systems

API design

Education

Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience

Tools

Terraform

GitOps

CI/CD

Job description

Cisco Systems, Inc. is seeking a Senior Platform Software Engineer for the Platform Engineering team to own architecture and operation of the control-plane and scheduling systems for multi-cluster GPU infrastructure.

You’ll shape scalable Kubernetes-based solutions, APIs, and workflows that manage tenant quotas and optimize training and inference workloads. The role combines deep systems software engineering with API design and operational leadership, mentoring engineers and driving reliability