Note: The job is a remote job and is open to candidates in USA. EY is a globally connected professional services organization focused on building a better working world. EY is seeking an AI Systems Engineer Manager to build and operate the infrastructure and cloud-native platform layers supporting its AI-native platform across cloud, on-premises, edge, and air-gapped environments. The role leads Kubernetes, GPU and bare-metal infrastructure, multi-tenancy, secure model execution, routing, disaster recovery, and platform automation.
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
- • Deep expertise in cloud-native platform engineering (Kubernetes, networking, multi-tenancy at scale) and low-level infrastructure and systems engineering (bare-metal, GPU, DPU)
- • Advanced understanding of how compute, networking, storage, and scheduling interact to form a reliable, portable substrate
- • Comfortable operating across cloud, on-prem, edge, and air-gapped environments simultaneously, with a portability-first mindset
- • Strong command of AI gateways, semantic routing, and model/prompt selection under latency and cost constraints
- • A passion for ensuring reliability, repeatability, and reduction of operational toil through automation and infrastructure-as-code
- • Ability to define and honor clean ownership boundaries with adjacent trust, data, and runtime teams
- • Strong communicator able to explain infrastructure tradeoffs to engineers, architects, and leadership
- • Natural product-ownership orientation toward foundational platforms, measured by the downstream velocity and reliability they enable
- • 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
- • Experience supporting AI/ML and GPU-intensive workloads (GPU virtualization, MIG, AI workload scheduling)
- • Experience with multi-tenant platforms and tenancy isolation at scale (e.g., vCluster)
- • Experience with disaster recovery, backup, and cross-environment replication tiered by RPO/RTO
- • Familiarity with distributed compute and batch orchestration (Kueue, Slurm/Slinky, Ray, OpenMPI)
- • Background in platform or SRE roles where success is measured by downstream team velocity, reliability, and portability
- • Exposure to regulated delivery environments (financial services, tax, healthcare, risk)
Benefits
- Medical and dental coverage
- Pension and 401(k) plans
- A wide range of paid time off options
- Team-led and leader-enabled hybrid model
- Under our flexible vacation policy, you’ll decide how much vacation time you need based on your own personal circumstances.
- Time off for designated EY Paid Holidays, Winter/Summer breaks, Personal/Family Care, and other leaves of absence when needed to support your physical, financial, and emotional well-being.
Company Overview
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