AI Platform Engineer: Delivery, Observability & FinOps

EY; Tucson (AZ); Hybrid; USD 113,000 - 138,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across cloud, on‑prem, edge, and air‑gapped environments. You will shape the AI-native platform, build automated pipelines, and govern AI assets with cost control and strong telemetry.

You’ll work across DevOps, MLOps, FinOps, and observability to ensure reproducible, compliant, and economical AI workloads with measurable performance and clear ownership boundaries.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI or high-throughput services.
• Hands-on DevOps experience including CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
• 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 tools and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.

Responsibilities

• Own DevOps and delivery for AI workloads with CI/CD/CV pipelines, including automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets, registries, and model metadata.
• Own resource and cost management with quotas and per-tenant attribution.
• Own the full observability stack: metrics, logs, traces, dashboards, and LLMS debugging.
• Own the OpenTelemetry collection layer across multi-tenant environments.
• Automate GitOps-based delivery and embed quality and cost gates in pipelines.
• Link delivery to observability through telemetry and cost signals for deployment decisions.
• Ensure consumption is attributable and regulated per tenant.

Skills

CI/CD pipelines

GitOps tooling

OpenTelemetry

GPU inference/serve

Observability stack

FinOps/cost attribution

Model governance

Clear communication

Education

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

Tools

ArgoCD

Helm

GitHub Actions/GitLab CI

Ray Serve

vLLM/Triton/NIM

Prometheus

Grafana

Loki

OpenTelemetry

Harbor

MLflow

Trivy

OpenLineage

Kubecost/OpenCost

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across cloud, on‑prem, edge, and air‑gapped environments. You will shape the AI-native platform, build automated pipelines, and govern AI assets with cost control and strong telemetry.

You’ll work across DevOps, MLOps, FinOps, and observability to ensure reproducible, compliant, and economical AI workloads with measurable performance and clear ownership boundaries.