AI Platform Engineer: DevOps, Observability & Governance

Ernst & Young Oman; Miami (FL); Hybrid; USD 107,000 - 177,000; Full time

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You’ll work within the Hybrid AI Runtime to shape how AI services are built, deployed, and governed, ensuring repeatable delivery and economical execution.

This role blends DevOps, MLOps, FinOps, and observability, requiring experience with GPU inference, multi-tenant cost attribution, and cross-environment pipelines in a regulated context.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on 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) for automated build, test, release, and rollback.
• 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.

Responsibilities

• Supports DevOps and delivery for AI workloads: build/operate CI/CD/CV pipelines and release processes to ship AI services and runtime components.
• Own governance and discovery for AI assets including registries, model metadata, and license management.
• Own resource and cost management including quotas and cost attribution for multi-tenant AI workloads.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA/alerting.
• Own OpenTelemetry collection and multi-tenant telemetry routing.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure cost/telemetry are per-tenant and accountable for FinOps goals.

Skills

DevOps expertise

MLOps experience

Observability

Cost optimization

Cloud platforms

Strong communication

Education

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

Tools

ArgoCD

Helm

GitHub Actions/GitLab CI

Ray Serve

vLLM

Triton

NIM

OpenTelemetry

Prometheus

Grafana

Loki

Tempo/Jaeger

Harbor

MLflow

Trivy

OpenLineage

LangSmith

Langfuse

DCGM

Envoy

Kubecost

OpenCost

HuggingFace

NGC

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You’ll work within the Hybrid AI Runtime to shape how AI services are built, deployed, and governed, ensuring repeatable delivery and economical execution.

This role blends DevOps, MLOps, FinOps, and observability, requiring experience with GPU inference, multi-tenant cost attribution, and cross-environment pipelines in a regulated context.