AI Platform DevOps & Observability Lead

EY

Toledo (OH)

Hybrid

USD 126,000 - 230,000

Full time

Just now
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Benefits offered by this job

Hybrid work model
Medical and dental coverage
Pension and 401(k)

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage CI/CD pipelines, secure model execution, and semantic routing across cloud and on-prem environments.

You will lead governance of AI assets, cost attribution, and telemetry, ensuring AI workloads are repeatable, compliant, and observable end-to-end. A strong background in DevOps, MLOps, and GPU inference is essential.

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 experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI, or equivalents).
  • Hands-on expertise with inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
  • Strong observability experience (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
  • Experience with API gateways and request routing (Envoy), including streaming responses.
  • Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).
  • Experience 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, including registries and metadata.
  • Own resource and cost management to keep AI execution economically bounded per tenant.
  • Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
  • Own the OpenTelemetry collection layer for multi-tenant environments.
  • Automate GitOps-based delivery and embed quality, cost, and integrity gates into pipelines.
  • Close the loop between delivery and observability to drive deployment decisions and rollbacks.
  • Ensure cost and telemetry are identity-stamped and per-tenant.

Skills

CI/CD/CV pipelines
GitOps tooling
Model serving
Observability
FinOps
Registries & scanning

Education

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

Tools

Ray Serve
vLLM/Triton/NIM
Prometheus/Grafana/Loki
OpenTelemetry
Harbor/MLflow/Trivy

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage CI/CD pipelines, secure model execution, and semantic routing across cloud and on-prem environments.

You will lead governance of AI assets, cost attribution, and telemetry, ensuring AI workloads are repeatable, compliant, and observable end-to-end. A strong background in DevOps, MLOps, and GPU inference is essential.

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