below marketmost similar roles pay hereabove market
This role pays more than
53%
of similar roles. Most pay
$151,000–$231,150
— the blue band above.
At the midpoint, this role pays about
$189k
versus about
$191k
for comparable roles.
Based on 240 similar postings.
Employer
About Cisco
Cisco Systems is the world''s leading networking technology company, designing and manufacturing networking hardware, telecommunications equipment, and cybersecurity solutions for businesses and governments. Industry: Networking Technology & Cybersecurity
Cisco currently has
307 open roles
on FindRole.
Listed pay typically runs
$167,700–$245,000
across 224 roles with salary data.
As a Platform Software Engineer on the Platform Engineering team, you will design, build, and operate the control-plane and scheduling systems for the AI Compute Platform. This role involves developing distributed systems, APIs, and controllers to manage multi-cluster environments, enforce tenant GPU quotas, and orchestrate complex training and inference workloads. You will build automated capacity-intake, demand-classification, and remediation tooling to maximize reliability and throughput across the GPU fleet. Key technologies include Go, Python, Kubernetes, OpenShift, Kubernetes Operators, CRDs, Terraform, and GitOps. You will also utilize observability tools like Splunk, Prometheus, and Grafana. The work focuses on solving the technical challenges of multi-tenant GPU infrastructure, including fractional allocation, workload-aware scheduling, and topology-aware placement for large-scale AI/ML model training and inference.
Design and develop platform control-plane services, APIs, and controllers to manage multi-cluster lifecycles and GPU quota enforcement.
Implement GPU capacity scheduling logic for fractional allocation, multi-tenant isolation, and workload-aware scheduling.
Build automated capacity-intake, demand-classification, and request-routing tooling to route workloads to appropriate compute pools.
Develop automated remediation tooling to detect node failures and optimize system-wide performance for training and inference.
Build and maintain scalable Kubernetes-based platforms using Operators, Controllers, CRDs, Go, and Python.
Implement Infrastructure as Code, GitOps, and CI/CD automation for the platform.
Develop internal tools and dashboards to improve platform visibility, efficiency, and reliability.
Participate in an on-call rotation to provide production infrastructure support and incident response.
What we're looking for
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 software development proficiency in Go or Python for building platform control-plane services, APIs, Kubernetes Controllers, Operators, or CRDs.
Hands-on experience building, configuring, or operating batch and accelerator schedulers for GPU or AI/ML workloads.
Practical experience with GPU scheduling, multi-tenant GPU infrastructure, or managing workloads on accelerated compute platforms.
Hands-on experience with Infrastructure as Code, GitOps, CI/CD deployment pipelines, and cloud-native observability tools.
Familiarity with multi-cluster control plane architectures, cluster registration/federation, and large-scale tenant isolation models (preferred).
Familiarity with modern data center GPU architectures and their scheduling and placement considerations (preferred).
Kubernetes
Go
Python
Linux
AWS
EKS
Terraform
Argo CD
Helm
Prometheus
Grafana
PyTorch
Ray
vLLM
SGLang
TensorRT-LLM
CUDA
NVLink
NVSwitch
NCCL
EFA
DCGM
Containers
HPC
Kubernetes
Go
Python
Linux
AWS
EKS
Terraform
Argo CD
Helm
Prometheus
Grafana
PyTorch
Ray
vLLM
SGLang
TensorRT-LLM
CUDA
NVLink
NVSwitch
NCCL
EFA
DCGM
HPC