AI Platform DevOps & Observability Lead

EY; Nashville (TN); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You will build and operate CI/CD pipelines, governance, cost visibility, and telemetry to ensure repeatable, compliant AI workloads across cloud, on-prem, edge, and air-gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on GPU inference, multi-env runtimes, and OpenTelemetry-based telemetry while aligning with

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 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).
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability experience (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalent), incl streaming responses.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost) and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
• Proven track record operating AI or service infrastructure under compliance constraints.
• Ability to define 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, agents, and runtime components.
• Own governance and discovery for AI assets, including service catalog/registry, experiment tracking, and model metadata.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization.
• Own the full observability stack: metrics, logs, traces, dashboards, and LangSmith/Langfuse for evaluation.
• Own the OpenTelemetry collection layer and multi-tenant telemetry routing.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability using telemetry and cost signals for deployment decisions.
• Ensure cost and telemetry are identity-stamped and per-tenant.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Communication

Education

Bachelor’s or Master’s in CS

Tools

Ray Serve

vLLM/Triton

NIM

Prometheus

Grafana

Loki

OpenTelemetry

Envoy

Harbor

MLflow

Trivy/SBOM

Kubecost/OpenCost

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You will build and operate CI/CD pipelines, governance, cost visibility, and telemetry to ensure repeatable, compliant AI workloads across cloud, on-prem, edge, and air-gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on GPU inference, multi-env runtimes, and OpenTelemetry-based telemetry while aligning with