Senior AI Platform Systems Engineer - Cloud & Kubernetes

EY; Tucson (AZ); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY seeks an AI Systems Engineer to own EY’s Hybrid AI multi-environment platform, spanning bare-metal, GPU, Kubernetes, and multi-tenant infra. You’ll manage cloud, on-prem, edge, and air-gapped environments, ensuring reliability and portability for regulated client contexts.

You will lead foundation capabilities, automate with IaC and GitOps, and collaborate with security, architecture, and product teams to deliver scalable, secure platforms that fuel EY’s AI initiatives.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related 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).
• 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).
• 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).
• Stand up and manage EY Agentic AI environments across cloud, on-prem AI Factory, edge, and air-gapped deployment modes.
• Deliver foundational platform capabilities such as Infrastructure Management, Kubernetes & Scheduling, and Cluster Fabric Management.
• Own cluster lifecycle, autoscaling, GPU pooling/virtualization, and multi-tenancy boundaries.
• Own secure execution and inference: Ray Serve, vLLM/NIM/Triton, and NVIDIA Dynamo, with 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, GitOps, Helm, ArgoCD to ensure reproducible environments.
• Own backup, disaster recovery, and cross-environment replication for high availability.
• Ensure modularity to minimize vendor lock-in while preserving stack contract.

Skills

Kubernetes

multi-tenancy

bare-metal

GPU infrastructure

infrastructure-as-code

GitOps

security/compliance

communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

RKE2

EKS/AKS/GKE

K3s

Terraform/OpenTofu

Helm

ArgoCD

Crossplane

Velero

Job description

EY seeks an AI Systems Engineer to own EY’s Hybrid AI multi-environment platform, spanning bare-metal, GPU, Kubernetes, and multi-tenant infra. You’ll manage cloud, on-prem, edge, and air-gapped environments, ensuring reliability and portability for regulated client contexts.

You will lead foundation capabilities, automate with IaC and GitOps, and collaborate with security, architecture, and product teams to deliver scalable, secure platforms that fuel EY’s AI initiatives.