AI Platform Engineer — DevOps, Observability & Governance

EY; San Francisco (CA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Hybrid work model

Generous PTO

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for its AI-native platform. You will manage CI/CD pipelines, governance of AI assets, and cost attribution while ensuring secure, compliant operation across cloud, on-prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong communication with engineers, architects, and leadership.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or 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 for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong experience with observability stacks and OpenTelemetry.
• Experience with API gateways and request routing, incl. streaming responses.
• Experience with cost management and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets and registries.
• Own resource and cost management with quotas and attribution.
• Own the full observability stack including metrics, logs, traces, dashboards, and SLA alerts.
• Own the OpenTelemetry collection layer across multi-tenant environments.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability by using telemetry and cost signals to drive deployment decisions.
• Ensure cost and telemetry are identity-stamped and per-tenant for end-to-end attribution.

Skills

DevOps

MLOps

Observability

Cost governance

OpenTelemetry

Model serving

CI/CD pipelines

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Artifactory/Nexus

Harbor

MLflow

HuggingFace/NGC

Trivy

OpenLineage

Prometheus

Grafana

Loki

Tempo/Jaeger

Envoy

Ray Serve

vLLM/Triton/NIM

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for its AI-native platform. You will manage CI/CD pipelines, governance of AI assets, and cost attribution while ensuring secure, compliant operation across cloud, on-prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong communication with engineers, architects, and leadership.