AI Systems Engineer — Delivery, Observability & MLOps

Ernst & Young Oman; Toledo (OH); Hybrid; USD 112,000 - 177,000; Full time

Job summary

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability across cloud, on-prem, edge, and air-gapped environments within the Hybrid AI Runtime. You will build CI/CD/CV pipelines, govern AI assets, and drive cost-aware delivery with a strong focus on governance and telemetry.

The role requires hands-on expertise in GPU inference serving, OpenTelemetry, and multi-tenant cost attribution, working with senior engineers to advance capabilities in a regulated

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Hands-on 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 stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with cost management/ FinOps tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.
• Proven track record operating AI or service infrastructure under compliance, security, or regulatory constraints.
• Ability to define clean ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Build and operate CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets with registries and MLflow.
• Manage resource costs, quotas, and per-tenant attribution.
• Own the full observability stack with metrics, logs, traces, and dashboards.
• Automate GitOps-based delivery and verification with policy gates.
• Drive deployment decisions via telemetry and cost signals.
• Ensure per-tenant cost attribution and FinOps alignment.
• Collaborate with senior engineers to test and extend capabilities.

Skills

DevOps expertise

MLOps experience

Observability engineering

Cost/FinOps mindset

Model governance familiarity

Multi-environment delivery

OpenTelemetry

AI workloads delivery

Education

Bachelor's or Master’s degree in CS or related field

Tools

ArgoCD

Helm

GitHub Actions / GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo / Jaeger

OpenTelemetry

LangSmith

Langfuse

Harbor

MLflow

Trivy

OpenLineage

Kubecost

OpenCost

DCGM

Job description

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability across cloud, on-prem, edge, and air-gapped environments within the Hybrid AI Runtime. You will build CI/CD/CV pipelines, govern AI assets, and drive cost-aware delivery with a strong focus on governance and telemetry.

The role requires hands-on expertise in GPU inference serving, OpenTelemetry, and multi-tenant cost attribution, working with senior engineers to advance capabilities in a regulated