AI Systems Engineer
US$125,500 – US$230,000 / yr base salary
Posted 25 Sep 2026
Advertised as “AI Systems Engineer - AI Platforms - Manager”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 8+ yrs
- Management level
- Individual contributor
- Employment
- Hybrid
| Base salary | US$125,500 – US$230,000 / yr |
|---|
Field of studyComputer Science (or related)
Study levelBachelor's or higher
Location: Anywhere in Country
At EY, we’re all in to shape your future with confidence.
We’ll help you succeed in a globally connected powerhouse of diverse teams and take your career wherever you want it to go. Join EY and help to build a better working world.
The opportunity
We are seeking AI Systems Engineers to build and operate the foundational substrate that powers EY’s AI-native platform. This role owns the infrastructure and cloud-native platform layers of the Hybrid AI Multi-Environment Runtime (HAI), from bare-metal and GPU infrastructure through Kubernetes, cluster fabric, and multi-tenant scaling. You will be responsible for building and managing EY Fabric environments across cloud, on-prem, edge, and air-gapped targets.
This is the substrate on which EY Agentic AI capabilities run. This role is ideal for a full-stack infrastructure leader who is equally comfortable with bare-metal and GPU systems and production Kubernetes at scale, who treats reliability and portability as non-negotiable in regulated client contexts, and who understands that the substrate is a product in its own right, measured by the velocity, safety, and portability it unlocks for every team building above it.
Your key 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.