AI Systems Engineer: DevOps, Model Serving & Observability

EY; Westlake Village (CA); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Paid time off options

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for an AI-native platform. You will work across cloud, on-prem, edge, and air-gapped environments, building automated pipelines, secure execution, and cost-attribution mechanisms.

You will own governance, registries, lineage, and Telemetry, while ensuring repeatable delivery with observability and FinOps aligned to tenant workloads. This hybrid role fits high-impact DevOps and MLOps owners.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI or high-throughput services.
• Hands-on CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Experience with inference/model-serving frameworks on GPU infrastructure.
• Strong observability stack experience (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing, including streaming responses.
• Familiarity with model/artifact registries and supply-chain scanning.
• Proven track record operating AI or service infrastructure under compliance and security constraints.
• Ability to define ownership boundaries and consumption contracts across teams.

Responsibilities

• Support DevOps and delivery for AI workloads with end-to-end pipelines and rollback capability.
• Own governance and discovery for AI assets, including registries and lineage tracking.
• Manage resource, cost, and quota controls to keep AI workloads economically bounded.
• Oversee the full observability stack and telemetry to support SLAs and cost visibility.
• Automate GitOps delivery and verification with policy gates in pipelines by default.
• Bridge delivery and observability using telemetry and cost signals for deployment decisions.

Skills

DevOps

MLOps

Observability

CI/CD pipelines

GitOps

OpenTelemetry

GPU inference

Cost management

Security/compliance

Model governance

Education

Bachelor’s or Master in Computer Science or related field

Tools

Ray Serve

vLLM/Triton/NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Harbor

MLflow

Trivy

Envoy

Kubecost/OpenCost

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for an AI-native platform. You will work across cloud, on-prem, edge, and air-gapped environments, building automated pipelines, secure execution, and cost-attribution mechanisms.

You will own governance, registries, lineage, and Telemetry, while ensuring repeatable delivery with observability and FinOps aligned to tenant workloads. This hybrid role fits high-impact DevOps and MLOps owners.