AI Platform DevOps & Observability Lead

EY; Phoenix (AZ); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Flexible vacation policy

Medical and dental coverage

Pension and 401(k)

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role spans enterprise-grade CI/CD, governance, cost visibility, and multi-tenant observability across cloud, on-prem, edge, and air-gapped environments.

You’ll lead automated release pipelines, secure model execution, and scalable telemetry while collaborating with platform, trust, and data teams to ensure compliant, repeatable AI workloads.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI or high-throughput services.
• Hands-on DevOps experience including CI/CD/CV pipelines and GitOps tooling.
• 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) and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate the CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with quotas and rate limits.
• Own the full observability stack: metrics, logs, traces, dashboards, and evaluation tooling.
• Own the OpenTelemetry collection layer for multi-tenant signals.
• Automate GitOps-based delivery with policy gates in pipelines.
• Close the loop between delivery and observability using telemetry and cost signals for deployments.
• Ensure cost and telemetry are identity-stamped per tenant.

Skills

DevOps expertise

MLOps experience

Observability

OpenTelemetry

Cost management mindset

Model governance & registries

Cloud & on-prem environments

Strong communication

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

Triton

Prometheus

Grafana

Loki

LangSmith

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role spans enterprise-grade CI/CD, governance, cost visibility, and multi-tenant observability across cloud, on-prem, edge, and air-gapped environments.

You’ll lead automated release pipelines, secure model execution, and scalable telemetry while collaborating with platform, trust, and data teams to ensure compliant, repeatable AI workloads.