AI Delivery & Observability Lead

EY; Dallas (TX); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for the AI-native platform across cloud, on-prem, edge, and air-gapped environments. You will build CI/CD/CV pipelines, secure model execution, and implement governance and cost visibility to keep workloads ship-ready and economical.

Ideal candidates have 8+ years in DevOps/MLOps with hands-on experience in GPU inference, model-serving frameworks, and OpenTelemetry.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on production ownership of AI or high-throughput services.
• Hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI, or equivalents) for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy) including streaming.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent) and quota enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
• Proven track record operating AI or service infrastructure under compliance, security, or regulatory constraints.
• Ability to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services and runtime components, with automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets, including registries, experiment tracking, and metadata.
• Own resource and cost management with quotas and attribution to keep AI execution economically bounded.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tooling.
• Own OpenTelemetry collection layer with multi-tenant support and reliable signal routing.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure per-tenant identity stamping for consumption and telemetry to tie FinOps to workloads.

Skills

DevOps

MLOps

Platform ownership

Observability

GitOps

CI/CD

GPU inference

OpenTelemetry

Cost optimization

Registry governance

Education

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

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Envoy

Harbor

MLflow

Trivy

Kubecost

OpenCost

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for the AI-native platform across cloud, on-prem, edge, and air-gapped environments. You will build CI/CD/CV pipelines, secure model execution, and implement governance and cost visibility to keep workloads ship-ready and economical.

Ideal candidates have 8+ years in DevOps/MLOps with hands-on experience in GPU inference, model-serving frameworks, and OpenTelemetry.