AI Systems Engineer: DevOps, Delivery & Observability

EY; Toledo (OH); Hybrid; USD 107,000 - 177,000; Full time

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 govern AI assets, optimize costs, and ensure secure, observable deployments across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong collaboration with engineers, architects, and leadership to drive repeatable, compliant AI workloads.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability with hands-on ownership of AI or high-throughput services.
• Strong hands-on DevOps experience, including CI/CD/CV pipelines and GitOps tooling.
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong experience with observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalent).
• Experience with cost management / FinOps tooling (OpenCost, Kubecost) and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).
• Proven track record operating AI or service infrastructure under compliance, security, or regulatory constraints.
• Ability to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Build and operate CI/CD/CV pipelines for AI workloads across environments.
• Own governance and discovery for AI assets and registries.
• Manage cost attribution and resource quotas for AI workloads.
• Own the full observability stack: metrics, logs, traces, dashboards.
• Manage OpenTelemetry collection layer and GPU telemetry.
• Automate GitOps-based delivery with policy gates.
• Drive deployment decisions via telemetry and cost signals to enable safe rollouts.
• Ensure per-tenant cost visibility and identity stamping across workloads.

Skills

DevOps pipelines

Model serving infra

Observability

FinOps mindset

Registries & scanning

Cloud/on‑prem edge

Communication skills

Education

Degree in CS

Tools

Ray Serve

vLLM/Triton/NIM

Envoy

Prometheus/Grafana/Loki

OpenTelemetry

Harbor/MLflow/Trivy

Kubecost/OpenCost

OpenLineage

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 govern AI assets, optimize costs, and ensure secure, observable deployments across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong collaboration with engineers, architects, and leadership to drive repeatable, compliant AI workloads.