AI Platform Lead: Hybrid Cloud & Kubernetes

EY; McLean (VA); Hybrid; USD 126,000 - 262,000; Full time

Benefits offered by this job

Competitive compensation

Hybrid work model

Flexible vacation policy

Job summary

EY seeks an AI Systems Engineer to build and operate the foundational substrate for EY’s AI-native platform. You’ll own the infrastructure and cloud-native layers, spanning bare-metal to Kubernetes, across cloud, on-prem, edge, and air-gapped environments.

The role demands leadership in platform reliability and portability, with a focus on speed, safety, and governance that enables teams to deploy AI workloads securely at scale.

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).
• 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 for Agentic AI workflows.
• 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, edge, and air-gapped deployment modes with 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.
• Own secure execution and inference: Ray Serve, vLLM/NIM/Triton, and NVIDIA Dynamo with sandboxing.
• Own cognitive and routing: Envoy AI Gateway, semantic routing, model/prompt selection, and streaming handling.
• Collaborate with DevOps on CI/CD/CV (ArgoCD), IaC/GitOps (Helm/OpenTofu), ensuring reproducible environments.
• Own backup, disaster recovery, and cross-environment replication with patching and supply-chain hygiene.
• Ensure the substrate is modular and swappable to minimize vendor lock-in.

Skills

Kubernetes expertise

Cloud-native platforms

Bare-metal & GPU infra

Multi-tenancy at scale

Security & compliance awareness

AI gateway knowledge

Automation & IaC

Communication with teams

Education

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

Tools

Terraform/OpenTofu

Helm

ArgoCD

Crossplane

Kubernetes distributions (RKE2/EKS/AKS/GKE)

Job description

EY seeks an AI Systems Engineer to build and operate the foundational substrate for EY’s AI-native platform. You’ll own the infrastructure and cloud-native layers, spanning bare-metal to Kubernetes, across cloud, on-prem, edge, and air-gapped environments.

The role demands leadership in platform reliability and portability, with a focus on speed, safety, and governance that enables teams to deploy AI workloads securely at scale.