AI Systems Engineer & DevOps — Deploy & Observe AI at Scale

EY; Miami (FL); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation & benefits

Paid time off

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing and observability for EY’s AI‑native platform. You’ll ship AI workloads with CI/CD pipelines, govern AI assets, and ensure cost visibility across cloud, on‑prem, edge and air‑gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, delivering repeatable AI workloads with governance and end‑to‑end traceability for budget‑aware deployments.

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 production ownership of AI or high‑throughput services.
• Strong hands‑on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI, or equivalents).
• 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.
• Experience with API gateways and request routing (Envoy or equivalent).
• Experience with cost management / FinOps tooling (OpenCost, Kubecost) and quota/rate‑limit enforcement.
• Familiarity with model/artifact registries and supply‑chain scanning (Harbor, MLflow, Trivy/SBOM).
• Proven track record operating AI or service infrastructure under compliance, security, or regulatory constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets, including registries and model metadata.
• Own resource and cost management, including quotas and attribution to tenants and engagements.
• Own the full observability stack: metrics, logs, traces, dashboards, and OpenTelemetry.”
• Own the OpenTelemetry collection layer and multi-tenant routing for signals and telemetry.
• Automate GitOps-based delivery and verification with policy gates in pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure cost and telemetry are per‑tenant and attributed end‑to‑end.

Skills

DevOps

MLOps

Platform engineering

Observability

CI/CD pipelines

GitOps tooling

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Kubecost

OpenCost

Harbor

MLflow

Trivy

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Envoy

Prometheus

Grafana

Loki

Tempo

Jaeger

Harbor

MLflow

Trivy

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing and observability for EY’s AI‑native platform. You’ll ship AI workloads with CI/CD pipelines, govern AI assets, and ensure cost visibility across cloud, on‑prem, edge and air‑gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, delivering repeatable AI workloads with governance and end‑to‑end traceability for budget‑aware deployments.