AI Systems Engineer & DevOps Observability Lead

Ernst & Young Advisory Services Sdn Bhd; Atlanta (GA); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage CI/CD/CV pipelines, governance of AI assets, and cost attribution across cloud, on-prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong communication with engineers, architects, and leadership. EY offers hybrid work and a broad rewards package.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Strong hands-on DevOps experience, including CI/CD/CV pipelines and GitOps tooling.
• Experience with OpenTelemetry, LangSmith/Langfuse for LLM evaluation and debugging.
• Familiarity with model/artifact registries, registry integrity, and license/lineage tracking.

Responsibilities

• Own DevOps and delivery for AI workloads; build and operate CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets, including registries, MLflow, and upstream registries.
• Own resource and cost management with quotas, attribution, and Kubecost/OpenCost.
• Own the full observability stack: Prometheus, Grafana, Loki, Tempo/Jaeger, and OpenTelemetry.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability using telemetry and cost signals.

Skills

DevOps engineering

MLOps

Observability

Cost optimization

Communication

Cloud platforms

Education

Bachelor’s or Master’s degree in Computer Science or related technical field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Envoy

Harbor

MLflow

Trivy

Kubecost

OpenCost

DCGM

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage CI/CD/CV pipelines, governance of AI assets, and cost attribution across cloud, on-prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong communication with engineers, architects, and leadership. EY offers hybrid work and a broad rewards package.