AI Platform Delivery & Observability Lead

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

Benefits offered by this job

Hybrid work model

Total rewards package: medical/dental,

401(k) plans

Job summary

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform across cloud, on-prem, edge, and air‑gapped environments. The role combines DevOps, MLOps, FinOps, and observability to ensure repeatable, economical AI workloads with policy‑driven release and rollback.

You will own the CI/CD/CV pipelines, governance for AI assets, cost attribution, and the full observability stack, including metrics, logs, traces, and dashboards.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related technical 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 for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong observability with metrics, logs, traces, and OpenTelemetry.
• Experience with API gateways and request routing including streaming responses.
• Experience with FinOps tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.

Responsibilities

• Own DevOps and delivery for AI workloads across CI/CD/CV pipelines and automated release processes.
• Own governance and discovery for AI assets and model metadata.
• Manage resource and cost attribution to keep AI execution economically bounded per tenant.
• Own the full observability stack including metrics, logs, traces, and dashboards.
• Oversee OpenTelemetry collection layer and multi-tenant telemetry routing.
• Automate GitOps-based delivery with policy‑driven quality and cost gates.
• Link delivery with telemetry to drive deployment decisions and automated rollbacks.
• Ensure per-tenant cost attribution and SLA/alerting for workloads.

Skills

DevOps

GitOps

MLOps

Observability

OpenTelemetry

GPU Inference

Education

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

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Harbor

MLflow

Trivy/SBOM

Job description

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform across cloud, on-prem, edge, and air‑gapped environments. The role combines DevOps, MLOps, FinOps, and observability to ensure repeatable, economical AI workloads with policy‑driven release and rollback.

You will own the CI/CD/CV pipelines, governance for AI assets, cost attribution, and the full observability stack, including metrics, logs, traces, and dashboards.