AI Systems Engineer: DevOps, Observability & FinOps

EY; Cleveland (OH); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Competitive compensation package

Generous time off

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. You will shape the runtime surface, governance, and cost visibility while collaborating with senior engineers to test and deploy capabilities.

This role spans DevOps, MLOps, FinOps, and observability, requiring strong CI/CD, model-serving, and cross‑environment cost visibility skills to ensure compliant, repeatable

Qualifications

• 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 for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong observability experience with Prometheus, Grafana, Loki and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalents).
• Experience with FinOps tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and scanning tools.
• Proven track record delivering AI/workload infrastructure under compliance and security constraints.
• Ability to define clean ownership boundaries and consumption contracts.

Responsibilities

• Supports DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets, including registries and metadata.
• Own resource and cost management to keep AI execution economically bounded per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI debugging tools.
• Own the OpenTelemetry collection layer and data routing for signals.
• Automate GitOps-based delivery with quality and cost gates in pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure per-tenant identity stamping for consumption signals and FinOps alignment.

Skills

DevOps

MLOps

Observability

FinOps

Cost management

Model governance

Registries

OpenTelemetry

GPU inference

CI/CD

Education

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

Tools

Envoy

Harbor

MLflow

Trivy

OpenLineage

LangSmith

Langfuse

Prometheus

Grafana

Loki

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. You will shape the runtime surface, governance, and cost visibility while collaborating with senior engineers to test and deploy capabilities.

This role spans DevOps, MLOps, FinOps, and observability, requiring strong CI/CD, model-serving, and cross‑environment cost visibility skills to ensure compliant, repeatable