AI Platform DevOps Engineer — Observability & Delivery

EY; Fort Worth (TX); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

401(k) and paid time off

Job summary

EY is seeking an AI Systems Engineer to own delivery, model serving, routing, and observability for the AI-native platform. You will oversee CI/CD/CV pipelines, governance of AI assets, and cost attribution across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong experience with GPUs, model serving, and multi-tenant cost controls. EY offers a hybrid work model and a comprehensive rewards package.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Strong hands-on DevOps experience, including 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 API gateways and request routing (Envoy or equivalent), including streaming responses.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent) 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: CI/CD/CV pipelines, automated build, test, verification, release, and rollback across environments.
• Own governance and discovery for AI assets including catalogs, registries, metadata, and license management.
• 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 signals and GPU telemetry.
• Automate GitOps-based delivery and continuous verification with policy-based gates.
• Close the loop between delivery and observability using telemetry and cost signals for rollout decisions.
• Ensure identity stamping and per-tenant attribution of cost and telemetry.

Skills

CI/CD pipelines

GitOps

ArgoCD

Helm

GitHub Actions

GitLab CI

AI model serving

GPU inference

OpenTelemetry

Ray Serve

vLLM

Triton

NIM

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Prometheus

Grafana

Loki

Tempo/Jaeger

Harbor

MLflow

Trivy

OpenLineage

Kubecost

OpenCost

Envoy

Job description

EY is seeking an AI Systems Engineer to own delivery, model serving, routing, and observability for the AI-native platform. You will oversee CI/CD/CV pipelines, governance of AI assets, and cost attribution across cloud, on‑prem, edge, and air‑gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong experience with GPUs, model serving, and multi-tenant cost controls. EY offers a hybrid work model and a comprehensive rewards package.