Remote AI Systems Engineer & DevOps Observability Lead

EY; Seattle (WA); Hybrid; USD 126,000 - 262,000; Full time

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. These are the systems that ship, run, and observably manage every AI workload in cloud, on‑prem, edge, and air‑gapped environments.

You will build automated delivery pipelines, govern AI assets, and manage cost attribution and telemetry to ensure repeatable, bounded AI execution at scale.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Hands-on DevOps 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 observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy) including streaming responses.
• Familiarity with cost tooling (OpenCost, Kubecost) and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
• Proven track record operating AI or service infrastructure under regulatory constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets, including registries and metadata.
• Own resource and cost management to keep AI execution bounded per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
• Own the OpenTelemetry collection layer and multi-tenant telemetry routing.
• Automate GitOps-based delivery and embed quality and cost gates in pipelines.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure consumption is identity-stamped and per-tenant for FinOps and observability.

Skills

DevOps pipelines

OpenTelemetry

Observability

Cost management

AI model serving

Education

Bachelor’s or Master’s in CS

Tools

Ray Serve

vLLM

Triton

NIM

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. These are the systems that ship, run, and observably manage every AI workload in cloud, on‑prem, edge, and air‑gapped environments.

You will build automated delivery pipelines, govern AI assets, and manage cost attribution and telemetry to ensure repeatable, bounded AI execution at scale.