AI Platform Engineer — DevOps & Observability Lead

EY; San Jose (CA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

401(k) plan

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 pipelines, governance of AI assets, and cost-aware deployment across cloud, on‑prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring deep expertise in GPUs, model serving, and multi-environment runtimes.

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 with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability experience with Prometheus, Grafana, Loki, Tempo/Jaeger and OpenTelemetry.
• Experience with API gateways and request routing (Envoy) including streaming responses.
• Experience with cost management tools (OpenCost, Kubecost) and quota/rate‑limit enforcement.
• Familiarity with model/artifact registries and registry scanning (Harbor, MLflow, Trivy/SBOM).
• Proven track record operating AI or service infrastructure under regulatory constraints.
• Ability to define ownership boundaries and consumption contracts across teams.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated release and rollback across environments.
• Own governance and discovery for AI assets, including registries, metadata, and lineage tools.
• Own resource and cost management with per-tenant attribution and quotas.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI debugging tools.
• Own OpenTelemetry collection and multi-tenant signal routing for reliable telemetry.
• Automate GitOps-based delivery and embed cost, quality and security gates in pipelines.
• Enable deployment decisions through telemetry, evaluation, and cost signals for safe rollouts and rollbacks.
• Ensure per-tenant identity stamping of cost and telemetry to support FinOps.

Skills

DevOps

MLOps

OpenTelemetry

Cost attribution

Model serving

GPU infrastructure

GitOps

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Envoy

Prometheus

Grafana

Loki

Jaeger

Trivy

MLflow

Harbor

OpenLineage

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 pipelines, governance of AI assets, and cost-aware deployment across cloud, on‑prem, edge, and air-gapped environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring deep expertise in GPUs, model serving, and multi-environment runtimes.