Senior AI Platform & Infrastructure Engineer – Hybrid Cloud

EY; Indianapolis (IN); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total rewards package

Flexible vacation policy

Job summary

EY is seeking an AI Systems Engineer to design and operate the foundational, cloud-native substrate for EY’s AI-native platform. You will own the Kubernetes layer, multi-tenant architecture, and GPU-enabled infrastructure across cloud, on‑prem, edge, and air‑gapped targets.

The role emphasizes reliability, portability, and regulatory compliance, with a track record in production infrastructure, IaC, and GitOps. EY offers a hybrid model and broad benefits in the US.

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.
• 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.
• 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.
• 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 Engineers on CI/CD/CV, IaC, and GitOps to ensure 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 while preserving the stack contract.

Skills

Kubernetes & cloud platforms

Bare-metal & GPU infra

Cluster networking & multi-tenancy

Infrastructure-as-code & GitOps

Security/compliance awareness

Cross-team collaboration

Education

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

Tools

RKE2

EKS/AKS/GKE

K3s

Terraform/OpenTofu

Helm

Job description

EY is seeking an AI Systems Engineer to design and operate the foundational, cloud-native substrate for EY’s AI-native platform. You will own the Kubernetes layer, multi-tenant architecture, and GPU-enabled infrastructure across cloud, on‑prem, edge, and air‑gapped targets.

The role emphasizes reliability, portability, and regulatory compliance, with a track record in production infrastructure, IaC, and GitOps. EY offers a hybrid model and broad benefits in the US.