AI Platform DevOps & Observability Engineer

EY; Louisville (KY); Hybrid; USD 107,000 - 177,000; Full time

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for the hybrid AI Runtime platform across cloud, on‑prem, and edge. Build automated pipelines, governance for AI assets, and cost attribution to keep workloads efficient and compliant.

This role blends DevOps, MLOps, FinOps, and observability, requiring GPU inference expertise, OpenTelemetry, and multi‑environment experience. EY offers a hybrid model and broad career growth.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI workloads.
• Hands-on CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Experience with inference/model-serving frameworks on GPU infrastructure.
• Strong observability stack knowledge and OpenTelemetry expertise.
• Familiarity with registries, governance, scanning, and license/lineage tracking.

Responsibilities

• Own the CI/CD/CV pipelines that ship AI services and runtime components across environments.
• Manage governance for AI assets, registries, and model metadata.
• Control resource cost, quotas, and attribution to keep AI execution bounded.
• Own the full observability stack: metrics, logs, traces, dashboards, and diagnostics.
• Automate GitOps-based delivery with policy-compliant gates and automated rollbacks.
• Bridge delivery and observability using telemetry to guide deployment decisions.
• Ensure per-tenant identity stamping for FinOps and telemetry.

Skills

DevOps

MLOps

Observability

FinOps

OpenTelemetry

Cost governance

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

LangSmith

Langfuse

Harbor

MLflow

Trivy

OpenLineage

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for the hybrid AI Runtime platform across cloud, on‑prem, and edge. Build automated pipelines, governance for AI assets, and cost attribution to keep workloads efficient and compliant.

This role blends DevOps, MLOps, FinOps, and observability, requiring GPU inference expertise, OpenTelemetry, and multi‑environment experience. EY offers a hybrid model and broad career growth.