AI Platform Delivery & Observability Lead

Ernst & Young Oman; Minneapolis (MN); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform across hybrid environments. You will build and operate CI/CD/CV pipelines, governance for AI assets, cost and telemetry signals, and an open telemetry stack to ensure secure, scalable model execution.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, requiring collaboration across cloud, on‑prem, edge, and regulated contexts.

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, including 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), including streaming responses.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent).
• 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.”
• Ability to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated build, test, release, and rollback for AI services and runtime components.
• Own governance and discovery for AI assets, including registries, experiment tracking, and license management.
• Own resource and cost management with quotas, rate limits, and per-tenant attribution.
• Own the full observability stack: metrics, logs, traces, dashboards, and OpenTelemetry integration.
• Own the OpenTelemetry collection layer across multi-tenant environments.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability using telemetry and cost signals to guide deployments.
• Ensure cost and telemetry are identity-stamped and per-tenant for accountable workloads.

Skills

DevOps

MLOps

Observability

GitOps

GPU inference

Cost management

OpenTelemetry

Model governance

Communication

Education

Bachelor’s or Master’s in CS or related

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

Triton

vLLM

Prometheus

Grafana

Loki

OpenLineage

Trivy

Kubecost

OpenCost

MLflow

Job description

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform across hybrid environments. You will build and operate CI/CD/CV pipelines, governance for AI assets, cost and telemetry signals, and an open telemetry stack to ensure secure, scalable model execution.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, requiring collaboration across cloud, on‑prem, edge, and regulated contexts.