AI Systems Engineer: DevOps, Observability & Governance

EY; Detroit (MI); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Medical and dental coverage

401(k) plan

Paid time off

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You will shape CI/CD/CV pipelines, governance, cost management, and multi-environment runtimes across cloud, on-prem, edge, and air-gapped environments.

You will work at the intersection of DevOps, MLOps, FinOps, and observability, enabling secure and repeatable AI workload delivery with strong emphasis on policy-compliant releases and end-to-end traceability.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering.
• Hands-on CI/CD/CV pipelines and GitOps tooling.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong observability stacks: Prometheus, Grafana, Loki, Tempo/Jaeger and OpenTelemetry.
• Experience with API gateways and request routing (Envoy).
• Experience with cost management / FinOps tooling (OpenCost, Kubecost).
• Familiarity with model/artifact registries and governance (Harbor, MLflow, Trivy).
• Proven track record operating AI or service infrastructure under compliance constraints.
• Ability to define clean ownership boundaries with platform/data/trust teams.

Responsibilities

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines, release, and rollback for AI services and runtimes.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with quota and rate limits to bound AI execution.
• 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 embedding quality and cost gates in pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure cost and telemetry are per-tenant and attributable across workloads.

Skills

DevOps pipelines

GitOps tooling

AI model serving

Observability stack

FinOps / cost attribution

Artifact governance

Multi-cloud / on-prem

Communication

Education

Bachelor’s/Master’s in Computer Science

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You will shape CI/CD/CV pipelines, governance, cost management, and multi-environment runtimes across cloud, on-prem, edge, and air-gapped environments.

You will work at the intersection of DevOps, MLOps, FinOps, and observability, enabling secure and repeatable AI workload delivery with strong emphasis on policy-compliant releases and end-to-end traceability.