Senior AI Platform Systems Engineer

EY; Minneapolis (MN); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Job summary

EY is seeking AI Systems Engineers to design and operate a scalable, cloud-native foundation for EY’s AI-native platform. You’ll own the Kubernetes layer, multi-tenant stack, and proximity to GPU-accelerated workloads across cloud, on-prem, edge, and air-gapped targets.

The role emphasizes reliability, portability, and regulatory compliance, with a hybrid working model and a strong emphasis on automation and IaC to reduce toil.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years building or operating enterprise infrastructure, cloud platforms, or large-scale Kubernetes environments.
• Hands-on expertise with Kubernetes distributions (RKE2, EKS/AKS/GKE, K3s) and full cluster lifecycle management.
• Deep experience with bare-metal, cloud, hybrid, on-prem, and ideally air-gapped deployment models.
• Strong grounding in cluster networking (Cilium/service mesh/CNI), storage, and multi-tenancy isolation.
• Experience with GPU infrastructure and scheduling (NVAIE/DCGM, GPU operators, virtualization/MIG).
• Experience with infrastructure-as-code and GitOps tooling (Terraform/OpenTofu, Helm, ArgoCD, Crossplane).
• Proven track record operating production infrastructure under compliance, security, or regulatory constraints.

Responsibilities

• Own the cluster & cloud-native platform: compute, Kubernetes and scheduling, cluster fabric/networking, multi-tenancy, and distributed compute.
• Own the infrastructure foundation: Ubuntu/OS, BMC/bare-metal, DPU architecture, and NVAIE (GPU/Network/DCGM), ensuring production readiness.
• Stand up EY Agentic AI environments across cloud, on-prem AI Factory, edge, and air-gapped modes with a consistent stack contract.
• Deliver foundational platform capabilities: Infrastructure Management, Kubernetes & Scheduling, and Cluster Fabric Management.
• Own cluster lifecycle, autoscaling, GPU pooling/virtualization, and multi-tenancy boundaries for isolated, elastic capacity.
• Own secure execution and inference with Ray Serve, vLLM/NIM/Triton, sandboxed execution for safety.
• Own cognitive and routing: Envoy AI Gateway, semantic routing, model/prompt selection, streaming responses.
• Collaborate with DevOps on CI/CD/CV, IaC/GitOps to ensure reproducible, drift-free environments.
• Own backup, disaster recovery, and cross-environment replication with Velero and related tooling.

Skills

Kubernetes

Cloud-native platform engineering

Multi-tenancy at scale

Infrastructure as code

GitOps

GPU infrastructure

Production Kubernetes

Education

Bachelor’s or Master’s degree in Computer Science or related technical field

Tools

RKE2

EKS/AKS/GKE

K3s

Terraform/OpenTofu

Helm

ArgoCD

Crossplane

Velero

Cilium

Karpenter

Job description

EY is seeking AI Systems Engineers to design and operate a scalable, cloud-native foundation for EY’s AI-native platform. You’ll own the Kubernetes layer, multi-tenant stack, and proximity to GPU-accelerated workloads across cloud, on-prem, edge, and air-gapped targets.

The role emphasizes reliability, portability, and regulatory compliance, with a hybrid working model and a strong emphasis on automation and IaC to reduce toil.