AI Systems Engineer & DevOps Observability Lead

EY; Arlington (VA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, spanning cloud, on‑prem, edge, and air‑gapped environments.

This senior role requires expertise in CI/CD pipelines, GPU inference, and full-stack observability, with a focus on secure, repeatable AI workload delivery and governance.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years in DevOps, MLOps, platform, or observability engineering, with hands-on ownership of AI or high-throughput services.
• Strong hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets and registries.
• Own resource and cost management with quotas and attribution.
• Own the full observability stack: metrics, logs, traces, dashboards.
• Own OpenTelemetry collection layer and multi-tenant telemetry routing.
• Automate GitOps-based delivery and verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions.

Skills

DevOps

MLOps

GitOps

Observability

Cost attribution

OpenTelemetry

GPU inference

Model serving

Ray Serve

Triton

vLLM

NIM

Prometheus

Grafana

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

OpenTelemetry

Prometheus

Grafana

Loki

Tempo/Jaeger

MLflow

Harbor

Trivy/SBOM

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, spanning cloud, on‑prem, edge, and air‑gapped environments.

This senior role requires expertise in CI/CD pipelines, GPU inference, and full-stack observability, with a focus on secure, repeatable AI workload delivery and governance.