AI Systems Engineer & DevOps Observability Lead

EY; Rogers (AR); Hybrid; USD 126,000 - 230,000; Full time

Job summary

EY seeks 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.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, handling CI/CD pipelines, governance, cost attribution, and telemetry to ensure repeatable, auditable AI workloads with secure execution across environments.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or a related technical field.
• 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 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).
• Experience with cost management / FinOps tooling (OpenCost, Kubecost).
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).
• Proven track record operating AI or service infrastructure under regulatory constraints.
• Ability to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines and release/rollback for AI services and runtimes.
• Own governance and discovery for AI assets, including registries, model metadata, and lineage.
• Own resource and cost management with quotas and attribution to tenants/workloads.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
• Own the OpenTelemetry collection layer for multi-tenant telemetry and GPU GPU telemetry.
• Automate GitOps-based delivery and verification with policy gates.
• Close the loop between delivery and observability using telemetry and cost signals.
• Ensure cost and telemetry are per-tenant and end-to-end traceable.

Skills

DevOps

MLOps

Observability

OpenTelemetry

CI/CD

GitOps

Model-serving

GPU inference

FinOps

Registries

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Envoy

OpenCost

Kubecost

Harbor

MLflow

Trivy

OpenLineage

LangSmith

Langfuse

DCGM

Job description

EY seeks 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.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, handling CI/CD pipelines, governance, cost attribution, and telemetry to ensure repeatable, auditable AI workloads with secure execution across environments.