AI Platform Engineer - DevOps, Observability & FinOps

EY; St. Louis (MO); On-site; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Paid time off

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. You’ll work across cloud, on-prem, edge, and air-gapped environments to ship, run, and observe AI workloads with automated pipelines and governance.

This role intersects DevOps, MLOps, FinOps, and observability, requiring 8+ years in related fields and hands-on experience with GPUs, model-serving frameworks, and cost management.

Qualifications

• 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) 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 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).
• 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 the delivery, model-serving, routing, and observability layer of EY’s AI-native platform across cloud, on-prem, edge, and air-gapped environments.
• Own governance and discovery for AI assets, model metadata, registries, and license management.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization.
• Own the full observability stack: metrics, logs, traces, dashboards, and OpenTelemetry.
• Own the OpenTelemetry collection layer, including multi-tenant receiver and exporters.
• Automate GitOps-based delivery and continuous verification with policy-based gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure identity-based cost telemetry and per-tenant attribution tied to workloads.

Skills

DevOps

MLOps

Observability

FinOps

OpenTelemetry

GPU Inference

Cost Attribution

GitOps

Model Governance

Education

Bachelor's or Master’s in CS/related

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Envoy

Harbor

MLflow

Trivy

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. You’ll work across cloud, on-prem, edge, and air-gapped environments to ship, run, and observe AI workloads with automated pipelines and governance.

This role intersects DevOps, MLOps, FinOps, and observability, requiring 8+ years in related fields and hands-on experience with GPUs, model-serving frameworks, and cost management.