AI Platform DevOps & Observability Leader

Ernst & Young Oman; Columbia (SC); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Hybrid work model

Paid time off

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. You will manage CI/CD/CV pipelines, governance of AI assets, and cost management across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on leadership in building automated delivery, secure model execution, and comprehensive telemetry.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related technical field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership of AI or high-throughput services.
• Hands-on DevOps experience including CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI) for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability experience (Prometheus, Grafana, Loki) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy) including streaming responses.
• Experience with cost management/FinOps tooling (OpenCost, Kubecost) and quota enforcement.
• Familiarity with model/artifact registries and supply-chain scanning (Harbor, MLflow, Trivy).
• Proven track record delivering AI or high‑throughput service infrastructure under regulatory constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services and runtime components; automate build, test, verification, release, and rollback.
• Own governance and discovery for AI assets: service catalogs, experiment tracking, model metadata, registries and licenses.
• Own resource and cost management with quotas and attribution to keep AI execution economical.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI debugging tools.
• Own the OpenTelemetry collection layer for multi-tenant telemetry and GPU telemetry.
• Automate GitOps-based delivery and verification with quality and cost gates.
• Drive deployment decisions with telemetry and cost signals; enable automated rollback when needed.
• Ensure cost and telemetry are per-tenant and attribution is maintained.

Skills

CI/CD pipelines

GitOps tooling

DevOps

MLOps

GPU inference

Observability

Education

Bachelor’s or Master’s degree in Computer Science or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

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. You will manage CI/CD/CV pipelines, governance of AI assets, and cost management across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on leadership in building automated delivery, secure model execution, and comprehensive telemetry.