Senior AI Platform Engineer: DevOps, Observability & FinOps

EY; Los Angeles (CA); On-site; USD 126,000 - 230,000; Full time

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability across EY’s hybrid runtime environment. You will build, operate, and govern the pipelines, assets, and telemetry that support lightweight, secure AI workloads at scale.

You will drive CI/CD/CV, governance for AI assets, cost attribution per tenant, and an end-to-end observability stack across cloud, on-prem, edge and air-gapped environments. Hybrid work expectations apply in the US.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability with production ownership of AI or high-throughput services.
• Hands-on experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability knowledge (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and cost management tooling (OpenCost, Kubecost) and quota controls.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
• Proven track record delivering AI/service infrastructure under regulated constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated build, test, release, and rollback.
• Own governance and discovery for AI assets, registries, model metadata, and license management.
• Own resource and cost management with quotas, rate limits, and per-tenant attribution.
• Own the full observability stack: metrics, logs, traces, dashboards, and evaluation tools.
• Own OpenTelemetry collection layer and multi-tenant routing and GPU telemetry.
• Automate GitOps-based delivery and embed quality and cost gates into pipelines.
• Close the loop between delivery and observability to drive deployments and automated rollbacks.
• Ensure cost and telemetry are tied to workloads for FinOps accountability.

Skills

DevOps pipelines

GitOps

MLOps

Observability

FinOps

Model governance

Education

Bachelor's degree in Computer Science or related field

Master's degree preferred

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability across EY’s hybrid runtime environment. You will build, operate, and govern the pipelines, assets, and telemetry that support lightweight, secure AI workloads at scale.

You will drive CI/CD/CV, governance for AI assets, cost attribution per tenant, and an end-to-end observability stack across cloud, on-prem, edge and air-gapped environments. Hybrid work expectations apply in the US.