AI Systems Engineer: DevOps, Delivery & Observability

EY

Houston (TX)

Ibrido

USD 107.000 - 177.000

Tempo pieno

14 giorni+

Una candidatura completa in un minuto

Curriculum e lettera di presentazione personalizzati, pronti da inviare.

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Vantaggi offerti da questo lavoro

Hybrid work model
Paid time off

Descrizione del lavoro

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across cloud, on‑prem, edge, and air‑gapped environments. You will shape the runtime surface, CI/CD/CV pipelines, and governance for AI workloads with a focus on repeatable, economical execution.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong GPU inference expertise, multi‑tenant cost attribution, and policy‑driven deployments.

Competenze

  • 8+ years in DevOps, MLOps, platform, or observability with hands-on ownership of AI/workloads.
  • Hands-on CI/CD pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
  • Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, NIM) on GPU.
  • Strong observability experience with Prometheus, Grafana, Loki, Tempo/Jaeger and OpenTelemetry.
  • Experience with API gateways and request routing (Envoy).
  • Experience with cost management tools (OpenCost, Kubecost) and quota enforcement.
  • Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
  • Proven track record in compliant AI/service infrastructure delivery.

Mansioni

  • Own delivery and runtime surface for AI workloads across environments.
  • Manage CI/CD/CV pipelines for AI services, including automated test and rollout.
  • Oversee governance and discovery for AI assets and registries.
  • Control cost attribution and utilization to keep AI workloads economical.
  • Own observability stack: metrics, logs, traces, dashboards.
  • Enforce policy gates in pipelines and enable automated rollbacks.
  • Collaborate across platform, trust, and data teams on ownership boundaries.

Conoscenze

DevOps for AI workloads
MLOps & observability
OpenTelemetry
GPU inference systems
Cost governance

Formazione

Bachelor's or Master's in CS or related

Strumenti

Ray Serve
vLLM
Triton
NIM
Prometheus
Grafana
OpenTelemetry
Kubecost
OpenCost
Envoy

Descrizione del lavoro

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across cloud, on‑prem, edge, and air‑gapped environments. You will shape the runtime surface, CI/CD/CV pipelines, and governance for AI workloads with a focus on repeatable, economical execution.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong GPU inference expertise, multi‑tenant cost attribution, and policy‑driven deployments.

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