AI Platform DevOps & Observability Lead

EY; Portland (OR); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical & dental coverage

Pension & 401(k)

Paid time off

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll build automated pipelines, secure model execution, and comprehensive telemetry across cloud, on‑prem, edge, and air‑gapped environments.

You will work at the intersection of DevOps, MLOps, FinOps, and observability, delivering high‑throughput AI workloads with repeatable, audited deployments.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with hands‑on production ownership of AI or high‑throughput services.
• Hands‑on DevOps experience with CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Hands‑on expertise operating inference/model‑serving frameworks on GPU infrastructure.
• Strong observability experience with Prometheus, Grafana, Loki and OpenTelemetry.
• Familiarity with registries, CVE scanning, and license/lineage tracking.

Responsibilities

• Own DevOps and delivery for AI workloads and CI/CD/CV pipelines for AI services.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with quota and rate‑limit enforcement.
• Own the full observability stack including metrics, logs, traces, and dashboards.
• Automate GitOps‑based delivery and ensure policy‑compliant releases.

Skills

DevOps

MLOps

OpenTelemetry

Prometheus

Grafana

Ray Serve

vLLM/Triton/NIM

CI/CD pipelines

GitOps

GPU inference

Education

Bachelor’s or Master’s degree in Computer Science

Tools

ArgoCD

Helm

GitHub Actions/GitLab CI

OpenTelemetry

Harbor/MLflow/Trivy

Prometheus/Grafana/Loki

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll build automated pipelines, secure model execution, and comprehensive telemetry across cloud, on‑prem, edge, and air‑gapped environments.

You will work at the intersection of DevOps, MLOps, FinOps, and observability, delivering high‑throughput AI workloads with repeatable, audited deployments.