AI Systems Engineer & DevOps Observability Leader

EY; Detroit (MI); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for an AI-native platform. You will ship AI workloads, govern assets, and drive cost visibility across cloud, on‑prem, edge, and air‑gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong ownership of pipelines, governance, and multi-tenant cost management.

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 production ownership of AI or high-throughput services.
• Strong hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI, or equivalents).
• 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).
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).
• Proven track record operating AI or service infrastructure under compliance and regulatory constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets including registries and metadata systems.
• Own resource and cost management to keep AI execution bounded per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and evaluation tooling.
• Own OpenTelemetry collection layer and multi-tenant signal routing.
• Automate GitOps-based delivery and verification with policy gates.
• Close the loop between delivery and observability to guide deployment decisions.
• Ensure cost and telemetry are identity-stamped and per-tenant for FinOps tracing.

Skills

DevOps expertise

MLOps experience

Observability

FinOps mindset

Governance & registries

Multi-cloud ops

Education

Bachelor’s or Master’s in CS or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

Triton

OpenTelemetry

Prometheus

Grafana

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for an AI-native platform. You will ship AI workloads, govern assets, and drive cost visibility across cloud, on‑prem, edge, and air‑gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong ownership of pipelines, governance, and multi-tenant cost management.