AI Platform Engineer: DevOps, Observability & Governance

Ernst & Young Oman; City of Albany (NY); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation

Total Rewards package

Flexible vacation policy

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform in cloud, on-prem, edge, and air-gapped environments. You will shape how AI services are built, deployed, and governed with robust CI/CD and cost controls.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong experience with GPUs, model serving, and end-to-end telemetry. Hybrid work and broad geographic scope apply.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI workloads.

Responsibilities

• Supports DevOps and delivery for AI workloads: build/run CI/CD/CV pipelines and release processes.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management to keep AI execution economical per tenant.
• Own the full observability stack: metrics, logs, traces, and AI debugging tools.
• Own the OpenTelemetry collection layer for reliable signal routing.
• Automate GitOps-based delivery and verification with policy gates.
• Drive deployment decisions using telemetry and cost signals for automated rollbacks.
• Ensure cost and telemetry are identity-stamped and per-tenant across workloads.

Skills

DevOps

MLOps

Platform engineering

Observability

CI/CD

GitOps

Ray Serve

OpenTelemetry

FinOps

Model governance

Education

Bachelor's or Master’s degree in Computer Science

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

LangSmith

Langfuse

OpenTelemetry

OpenCost

Kubecost

Harbor

MLflow

Trivy

OpenLineage

Envoy

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform in cloud, on-prem, edge, and air-gapped environments. You will shape how AI services are built, deployed, and governed with robust CI/CD and cost controls.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong experience with GPUs, model serving, and end-to-end telemetry. Hybrid work and broad geographic scope apply.