Senior AI Platform Engineer & Leader

EY

Houston (TX)

On-site

USD 144,000 - 329,000

Full time

3 days ago

Be an early applicant

A complete application in a minute

Tailored resume and cover letter, ready to send.

Get past ATS filters

Job summary

EY is seeking a senior leader for its AI Platform Engineering group to lead the infrastructure and cloud-native platform powering EY’s AI runtime. You will set technical direction, guide a team of AI Infrastructure and AI Systems Engineers, and personally design and troubleshoot critical platform components across cloud, on-prem, edge, and air-gapped targets.

This player-coach role requires hands-on contribution, phased roadmaps, and a focus on reliability and portability in regulated client

Qualifications

Bachelor’s or Master’s degree in Computer Science or a related technical field.
10+ years building or operating enterprise infrastructure, cloud platforms, or large-scale Kubernetes environments, with hands-on depth.
3+ years leading or directing engineering teams while remaining an active contributor.
Track record of owning a platform or infrastructure roadmap and architecture end-to-end.
Hands-on experience with Kubernetes distributions (RKE2, EKS/AKS/GKE, K3s) and full cluster lifecycle management.
Experience with bare-metal, cloud, hybrid, on-prem, and ideally air-gapped deployment models.
Strong understanding of security, compliance, and incident response in regulated contexts.
Experience using infrastructure-as-code and GitOps tooling (Terraform/OpenTofu, Helm, ArgoCD).
Ability to work with security, architecture, product, and delivery teams and defend technical decisions to leadership.

Responsibilities

Lead and develop the AI Platform Infrastructure Engineering team: direct day-to-day work, hire, mentor, set standards, and grow leadership.
Design, implement, and debug the hardest platform components—cluster bring-up, GPU/networking, multi-tenancy, inference and routing.
Own the infrastructure delivery roadmap and report progress, risks, and trade-offs to senior leadership.
Oversee the infrastructure foundation and cloud-native platform across compute, Kubernetes, scheduling, and multi-tenancy.
Stand up and operate EY Agentic AI environments across cloud, on-prem, edge, client-managed, and air-gapped modes.
Own secure execution, inference, and routing with Ray Serve, vLLM/NIM/Triton, and NVIDIA tools; manage model routing and sandboxing.
Define SLOs, incident management, backup, DR, and cross-environment replication; partner on CI/CD/CV and GitOps to ensure reproducibility.
Forecast demand, manage budgets, evaluate vendor options, and justify capacity to leadership.