Senior AI Systems Engineer — Hybrid Delivery & Observability

EY; Dallas (TX); Hybrid; USD 107.000 - 201.000; Vollzeit

Benefits dieser Stelle

Hybrid work model

Medical and dental coverage

401(k) plan with company match

Paid time off

Zusammenfassung

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You will shape how AI services are built, deployed, and observed across cloud, on‑prem, and edge environments, enabling cost-aware, repeatable workloads.

You will work across DevOps, MLOps, FinOps, and observability to design pipelines, governance, and telemetry that keep AI workloads secure, compliant, and efficiently deployed at scale.

Qualifikationen

• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI workloads.
• Hands-on CI/CD/CV pipelines and GitOps tooling for automated delivery and rollback.
• Experience with inference frameworks (Ray Serve, vLLM, Triton, NIM) on GPUs.
• Strong observability skills across metrics, logs, and traces.
• Familiarity with model registries, CVE scanning, and license/lineage tracking.

Aufgaben

• Build and operate CI/CD/CV pipelines to ship AI services and runtime components.
• Own governance and discovery for AI assets and registries.
• Manage resource, quotas, and cost attribution to keep AI workloads bounded.
• Own full observability stack: metrics, logs, traces, dashboards.
• Automate GitOps delivery with quality and cost gates in pipelines.
• Ensure end-to-end telemetry and cost signals guide deployment decisions.

Kenntnisse

DevOps

MLOps

Observability

GitOps

CI/CD

Cost attribution

GPU inference

OpenTelemetry

Communication

Ausbildung

Bachelor’s or Master’s in CS

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM/Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

LangSmith/Langfuse

OpenTelemetry

Harbor/MLflow/Trivy

Kubecost/OpenCost

Envoy

Jobbeschreibung

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You will shape how AI services are built, deployed, and observed across cloud, on‑prem, and edge environments, enabling cost-aware, repeatable workloads.

You will work across DevOps, MLOps, FinOps, and observability to design pipelines, governance, and telemetry that keep AI workloads secure, compliant, and efficiently deployed at scale.