Senior AI Systems Engineer: Platform Delivery & Observability

Ernst & Young Oman; Austin (TX); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Medical and dental coverage

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, delivering repeatable AI workloads across cloud, on-prem, edge, and air-gapped environments.

The ideal candidate will lead CI/CD/CV pipelines, governance for AI assets, and full observability, while ensuring cost attribution and policy-compliant releases in a hybrid work model at EY.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering, with hands-on production ownership of AI or high-throughput services.
• 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 observability experience with metrics, logs, traces and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalent).
• Experience with cost management tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and governance tools.

Responsibilities

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines delivering AI services and runtime components.
• Own governance and discovery for AI assets, including registries, model metadata, and license management.
• Own resource and cost management to ensure AI execution stays bounded and attributable.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA alerts.
• Own OpenTelemetry collection layer and multi-tenant signal routing for GPU telemetry.
• Automate GitOps-based delivery and verification with quality and cost gates.
• Close the loop between delivery and observability to guide deployment decisions and rollbacks.
• Ensure cost and telemetry are identity-stamped and per-tenant.

Skills

DevOps

MLOps

Observability

FinOps

GPU delivery

Communication

Education

Bachelor's or Master's in Computer Science or related field

Tools

Ray Serve

vLLM

Triton

NIM

OpenTelemetry

Envoy

Kubecost/OpenCost

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, delivering repeatable AI workloads across cloud, on-prem, edge, and air-gapped environments.

The ideal candidate will lead CI/CD/CV pipelines, governance for AI assets, and full observability, while ensuring cost attribution and policy-compliant releases in a hybrid work model at EY.