Platform Software Engineer – AI/ML, GPU Infrastructure

Cisco

. Design and develop platform control-plane services, APIs, and controllers for multi-cluster lifecycle, tenant project onboarding, and GPU quota enforcement .

Posted 10/22/2026full-timeUnited StatesMid-LevelSenior💰 $155,000 - $222,600 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and developing Kubernetes-based platforms, focusing on control-plane services, GPU scheduling, and automation. Proficient in implementing Infrastructure as Code and CI/CD practices to enhance system performance and reliability.

Highest-signal resume keywords

Kubernetes-Based Platform DevelopmentGo ProgrammingGPU Scheduling ExperienceInfrastructure as Code (Terraform)CI/CD Automation

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Kubernetes ControllersCustom APIsKubernetes OperatorsCRDsBatch SchedulersGPU Quota EnforcementAutomated Remediation ToolingDemand-Classification ToolingWorkload-OrchestrationCLI Utilities

Soft Skills

CollaborationIncident ResponseProblem-Solving

Tools & Technologies

OpenShiftSplunkPrometheusGrafanaGitOps

Industry Keywords

Multi-Cluster LifecycleAI/ML InfrastructureTenant Isolation ModelsNVIDIA H100Distributed Systems

Tech Stack

Tools & technologies

CloudDistributed SystemsGrafanaKubernetesNode.jsOpenShiftPrometheusPythonSplunkTerraformGo

About the role

Key responsibilities & impact

Design and develop platform control-plane services, APIs, and controllers for multi-cluster lifecycle, tenant project onboarding, and GPU quota enforcement
Implement GPU capacity scheduling and allocation, including fractional GPU allocation, multi-tenant isolation, and workload-aware scheduling
Build capacity-intake, demand-classification, and request-routing tooling for clusters and compute pools
Build automated remediation tooling for node and workload failures
Optimize system-wide performance for training and inference workloads
Design, build, and maintain scalable Kubernetes-based platforms using OpenShift or upstream Kubernetes
Develop platform services and automation using Kubernetes Operators, Controllers, CRDs, Go, and Python
Develop platform automation, internal tools, and dashboards to improve visibility, efficiency, and reliability
Implement Infrastructure as Code, GitOps, and CI/CD automation
Participate in an on-call rotation
Collaborate with infrastructure, hardware, and engineering teams to operate Cisco’s AI Compute Platform

Requirements

What you’ll need

Bachelor's degree in Computer Science, Computer Engineering, or equivalent practical experience
5+ years of software engineering experience building, operating, or extending Kubernetes-based platforms or distributed systems
Strong proficiency in Go or Python
Hands-on experience building platform control-plane services, custom APIs, Kubernetes Controllers, Operators, or CRDs
Hands-on experience with batch and accelerator schedulers such as Kueue, Volcano, Slurm, or custom scheduler plugins for GPU or AI/ML workloads
Practical experience with GPU scheduling, multi-tenant GPU infrastructure, or accelerated compute platforms
Hands-on experience with Infrastructure as Code such as Terraform, GitOps, CI/CD deployment pipelines, and cloud-native observability tools such as Splunk, Prometheus, and Grafana
Familiarity with multi-cluster control plane architectures, cluster registration/federation, and large-scale tenant isolation models
Familiarity with modern data center GPU architectures such as NVIDIA H100, H200, B200/B300, or AMD Instinct accelerators
Familiarity with topology-aware placement, NCCL, and gang scheduling for multi-node training clusters
Experience supporting AI/ML infrastructure, including model serving pipelines, distributed training, workload orchestration, or MLOps platforms
Experience building automated capacity-intake, demand-classification, or request-routing tooling
Experience developing engineering-focused developer tools, CLI utilities, or dashboards
Exposure to Kubernetes control plane internals, including API server, etcd, controller-manager, and scheduler framework
Experience participating in on-call rotations, incident response, and postmortem/runbook processes for production infrastructure

Benefits

Comp & perks

Medical, dental and vision insurance
401(k) plan with a Cisco matching contribution
Paid parental leave
Short- and long-term disability coverage
Basic life insurance
Cisco restricted stock unit grants may be available, subject to eligibility and continued employment
10 paid holidays per full calendar year
1 floating holiday for non-exempt employees
1 paid day off for employee’s birthday
Paid year-end holiday shutdown
4 paid days off for personal wellness
16 days of paid vacation time per full calendar year for non-exempt employees
Flexible vacation time off program with no defined limit for eligible exempt employees
80 hours of sick time off provided on hire date and each January 1st thereafter
Up to 80 hours of unused sick time carried forward
Additional paid time away for critical or emergency family issues
Optional 10 paid volunteer days per full calendar year
Annual bonuses for non-sales roles, subject to Cisco’s policies
Sales incentive compensation for employees on sales plans, subject to applicable Cisco plan