Remote-Ready AI Systems Engineer & DevOps Observability

EY; Jericho (NY); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical coverage

Pension/401(k)

Paid time off

Hybrid work model

Flexible vacation policy

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. The role spans CI/CD, governance, cost management, and end-to-end observability across cloud, on-prem, edge, and air-gapped environments.

You will work across DevOps, MLOps, FinOps, and trust teams to ensure repeatable, scalable AI workloads. This senior engineering position requires 8+ years in DevOps or related fields, hands-on GPU inference, and strong OpenTelemetry

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.
• Strong hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
• 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) and streaming responses.
• Experience with cost management / FinOps tooling 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 and security 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 and release/rollback for AI services and runtime components.
• Own governance and discovery for AI assets, including registries, experiment tracking, and metadata.
• Own resource and cost management, including quotas and cost attribution per tenant and engagement.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA/alerts.
• Own the OpenTelemetry collection layer and GPU telemetry integration.
• Automate GitOps-based delivery and verification with policy gates in pipelines.
• Close the loop between delivery and observability using telemetry and cost signals for deployment decisions.
• Ensure consumption is identity-stamped and per-tenant for FinOps and observability tied to workloads.

Skills

DevOps

MLOps

Observability

OpenTelemetry

Cost management

Model governance

Multi-cloud

GitOps

CI/CD pipelines

GPU inference

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

LangSmith

Langfuse

OpenTelemetry

Harbor

MLflow

Trivy

SBOM

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. The role spans CI/CD, governance, cost management, and end-to-end observability across cloud, on-prem, edge, and air-gapped environments.

You will work across DevOps, MLOps, FinOps, and trust teams to ensure repeatable, scalable AI workloads. This senior engineering position requires 8+ years in DevOps or related fields, hands-on GPU inference, and strong OpenTelemetry