AI Systems DevOps Engineer – Platform & Observability

EY; Tulsa (OK); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will oversee how AI services are built, deployed, and observed across cloud, on‑prem, edge, and air‑gapped environments.

This role combines DevOps, MLOps, FinOps, and observability, requiring hands-on experience with GPU inference, CI/CD pipelines, and modern telemetry to ensure repeatable, cost‑aware AI workloads in a hybrid work model.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on 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 stack experience (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalent).
• Experience with cost management / FinOps tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines for AI services and runtimes.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with tenant-bound controls.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
• Own the OpenTelemetry collection layer and multi-tenant telemetry routing.
• Automate GitOps-based delivery and ensure policy-compliant releases by default.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure consumption is attributable and FinOps-aligned across workloads.

Skills

DevOps

MLOps

Observability

GitOps

CI/CD

OpenTelemetry

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Prometheus

Grafana

Loki

Tempo/Jaeger

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will oversee how AI services are built, deployed, and observed across cloud, on‑prem, edge, and air‑gapped environments.

This role combines DevOps, MLOps, FinOps, and observability, requiring hands-on experience with GPU inference, CI/CD pipelines, and modern telemetry to ensure repeatable, cost‑aware AI workloads in a hybrid work model.