Senior AI DevOps & Observability Engineer

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

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY''s AI-platform. You will shape the CI/CD pipelines, secure model execution, and ensure economical, auditable AI workloads across cloud, on-prem, edge, and air-gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, requiring deep expertise in inference systems, registries, and governance, with a strong focus on cost attribution and per-tenant

Qualifications

• 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 (ArgoCD, Helm, GitHub Actions/GitLab CI or equivalents).
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong experience with observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost) and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy/SBOM).
• 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

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services, agents, and runtime components, including automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets, including service catalogs/registries, experiment tracking, and model metadata, along with CVE/SBOM scanning and license management.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization to keep AI execution economically bounded per tenant and engagement.
• Own the full observability stack: metrics, logs, traces, dashboards, and LL M debugging/evaluation.
• Own the OpenTelemetry collection layer for multi-tenant signal capture and reliable routing.
• Automate GitOps-based delivery and continuous verification with quality, integrity, and cost gates.
• Close the loop between delivery and observability using telemetry and cost signals to drive deployment decisions and automated rollback.
• Ensure cost and telemetry are identity-stamped and per-tenant for accountable consumption.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Multi-cloud

Education

Bachelor's degree in Computer Science or related field

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Harbor

MLflow

Trivy

Kubecost

OpenCost

LangSmith

Langfuse

Envoy

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY''s AI-platform. You will shape the CI/CD pipelines, secure model execution, and ensure economical, auditable AI workloads across cloud, on-prem, edge, and air-gapped environments.

This role sits at the intersection of DevOps, MLOps, FinOps and observability, requiring deep expertise in inference systems, registries, and governance, with a strong focus on cost attribution and per-tenant