Senior AI Platform Infrastructure Engineer

EY; Washington (District of Columbia); On-site; USD 151,000 - 262,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k) plans

Paid time off

Job summary

EY is seeking an AI Systems Engineer to build and operate a cloud-native, multi-tenant substrate powering EY's AI-native platform. You will manage Kubernetes, bare-metal and GPU infrastructure, across cloud, on-prem, edge, and air-gapped targets, delivering a portable, scalable foundation for AI workloads.

You will own infrastructure, automation, and security while collaborating with DevOps, security, and product teams to ensure reliability and portability in regulated client contexts.

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, including hands-on systems depth.
• 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.
• Ability to work effectively with security, architecture, product, and delivery teams.

Responsibilities

• Own the cluster & cloud-native platform: compute, Kubernetes and scheduling, cluster fabric/networking, multi-tenancy, and distributed compute, as the substrate for Agentic AI workflows and tooling.
• Own the infrastructure foundation: Ubuntu/OS, BMC/bare-metal, DPU architecture, and NVAIE (GPU/Network/DCGM), ensuring the physical and virtual bedrock is provisioned, patched, and production-ready.
• Stand up and manage EY Agentic AI environments across cloud (EKS/AKS/GKE), on-prem AI Factory (RKE2/NVAIE), edge (K3s), and air-gapped deployment modes, maintaining one consistent stack contract across all targets.
• Deliver foundational platform capabilities such as Infrastructure Management, Kubernetes & Scheduling, and Cluster Fabric Management, so downstream runtime, data, and execution services can run safely and consistently.
• Own cluster lifecycle, autoscaling, GPU pooling/virtualization, and multi-tenancy boundaries (vCluster/Crossplane/Karpenter), providing isolated, elastic capacity per tenant and engagement.
• Own secure execution and inference: Ray Serve, vLLM/NIM/Triton, and NVIDIA Dynamo, with sandboxed execution (gVisor/Firecracker for hosted, NVIDIA OpenShell/vNode for on-prem) for isolated, safe model execution.
• Own cognitive and routing: Envoy AI Gateway, semantic routing (vLLM-SR), model/prompt selection, and streaming response handling — directing each request to the right model under the right constraints.
• Collaborate with DevOps Engineers on deployment and delivery of the platform itself: CI/CD/CV (ArgoCD), infrastructure-as-code / GitOps (Helm/OpenTofu), so environments are reproducible and drift-free.
• Own backup, disaster recovery, and cross-environment replication for high availability (Velero, CloudNativePG, Cilium ClusterMesh), along with patching and platform supply-chain hygiene.
• Ensure the substrate is modular and swappable, so components can be replaced without rewriting consumers, minimizing vendor lock-in while preserving the stack contract.

Skills

Kubernetes

Multi-tenancy

Cloud platforms

Bare-metal & GPU infra

Infrastructure as code

GitOps

Security & compliance

Education

Bachelor’s or Master’s in Computer Science

Tools

RKE2

EKS/AKS/GKE

K3s

Terraform/OpenTofu

Helm

ArgoCD

Crossplane

Job description

EY is seeking an AI Systems Engineer to build and operate a cloud-native, multi-tenant substrate powering EY's AI-native platform. You will manage Kubernetes, bare-metal and GPU infrastructure, across cloud, on-prem, edge, and air-gapped targets, delivering a portable, scalable foundation for AI workloads.

You will own infrastructure, automation, and security while collaborating with DevOps, security, and product teams to ensure reliability and portability in regulated client contexts.