AI Systems Platform Engineering Lead

EY; Memphis (TN); Hybrid; USD 126,000 - 262,000; Full time

Benefits offered by this job

Hybrid model

Competitive compensation

Flexible vacation policy

Job summary

EY is seeking AI Systems Engineers to architect and operate a cloud-native platform powering the EY Agentic AI capabilities. You will manage Kubernetes, bare-metal and GPU infrastructure spanning cloud, on-prem, edge, and air-gapped environments, delivering a portable, reliable substrate for AI workloads.

The role emphasizes scalable multi-tenant design, security, and automation with IaC and GitOps, while aligning with regulatory constraints and enterprise needs.

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).
• Stand up and manage EY Agentic AI environments across cloud, on-prem AI Factory, edge, and air-gapped deployment modes, maintaining a consistent stack contract.
• 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 for isolated capacity.
• Own secure execution and inference with sandboxed execution for model safety.
• Own cognitive and routing: Envoy AI Gateway, semantic routing, model/prompt selection, streaming responses.
• Collaborate with DevOps on CI/CD/CV, IaC/GitOps for reproducible environments.
• Own backup, disaster recovery, and cross-environment replication for high availability.
• Ensure the substrate is modular and swappable to minimize vendor lock-in.

Skills

Cloud-native platform engineering

Kubernetes & multi-tenancy

Bare-metal & GPU infrastructure

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Kubernetes distributions (RKE2, EKS/AKS/GKE, K3s)

Terraform/OpenTofu, Helm, ArgoCD, Crossplane

Job description

EY is seeking AI Systems Engineers to architect and operate a cloud-native platform powering the EY Agentic AI capabilities. You will manage Kubernetes, bare-metal and GPU infrastructure spanning cloud, on-prem, edge, and air-gapped environments, delivering a portable, reliable substrate for AI workloads.

The role emphasizes scalable multi-tenant design, security, and automation with IaC and GitOps, while aligning with regulatory constraints and enterprise needs.