AI Systems Engineer: DevOps, Observability & FinOps

EY; Chicago (IL); Hybrid; USD 107,000 - 177,000; Full time

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 across cloud, on‑prem, edge, and air‑gapped environments. This role requires building automated delivery pipelines, operating high‑performance inference, and deep observability with cost visibility.

The candidate will work at the intersection of DevOps, MLOps, FinOps, and observability, ensuring repeatable, auditable AI workloads with governance and secure

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with ownership of AI or high-throughput services.
• Strong 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.
• Observability stacks experience: 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 and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.
• Proven track record operating AI or service infrastructure under regulatory constraints.

Responsibilities

• Supports DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated build, test, release, and rollback.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with quotas and cost attribution across tenants.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA/alerting.
• Own the OpenTelemetry collection layer and multi-tenant signals for reliable routing.
• Automate GitOps-based delivery and embedding quality and cost gates into pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure per-tenant identity stamping and cost telemetry across workloads.

Skills

CI/CD pipelines

GitOps tooling

OpenTelemetry

GPU inference / model serving

Observability stacks

FinOps / cost attribution

Model governance

API gateways (Envoy)

Multi-tenant / regulated environments

Education

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

Tools

Ray Serve

vLLM

Triton

NIM

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 across cloud, on‑prem, edge, and air‑gapped environments. This role requires building automated delivery pipelines, operating high‑performance inference, and deep observability with cost visibility.

The candidate will work at the intersection of DevOps, MLOps, FinOps, and observability, ensuring repeatable, auditable AI workloads with governance and secure