AI Platform Engineer: Delivery, Observability & FinOps

EY; Richmond (VA); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k) plans

Paid time off options

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across hybrid environments. You’ll shape the runtime surface and CI/CD pipelines for secure AI workloads, spanning cloud, on-prem, edge, and air-gapped setups, collaborating with senior engineers to test and develop capabilities.

You’ll operate across DevOps, MLOps, FinOps, and observability with a focus on governance, cost visibility, and scalable, reproducible AI delivery at scale.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with production ownership.
• Hands-on DevOps: CI/CD/CV pipelines and GitOps tooling for automated build, test, release, rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Observability stacks and OpenTelemetry experience.
• Cost management tools and quota/rate-limit enforcement experience.
• Familiarity with registries and scanning (Harbor, MLflow, Trivy/SBOM).
• Proven experience in AI/service infrastructure under regulatory constraints.
• Ability to define ownership boundaries with platform, trust, and data teams.

Responsibilities

• Supports DevOps and delivery for AI workloads: CI/CD/CV pipelines and automated release and rollback.
• Own governance and discovery for AI assets and model metadata.
• Own cost attribution and utilization to keep AI execution bounded per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI debugging tools.
• Own OpenTelemetry collection and multi-tenant telemetry routing.
• Automate GitOps-based delivery and embed gates for policy compliance.
• Close loop between delivery and observability to drive deployment decisions and rollback.
• Ensure cost and telemetry are identity-stamped and per-tenant.

Skills

DevOps

MLOps

Observability

OpenTelemetry

FinOps

Model governance

GPU inference

Registry & scanning

Education

Bachelor’s or Master’s in CS or related

Tools

Ray Serve

vLLM/Triton/NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Envoy

Harbor/MLflow/Trivy

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across hybrid environments. You’ll shape the runtime surface and CI/CD pipelines for secure AI workloads, spanning cloud, on-prem, edge, and air-gapped setups, collaborating with senior engineers to test and develop capabilities.

You’ll operate across DevOps, MLOps, FinOps, and observability with a focus on governance, cost visibility, and scalable, reproducible AI delivery at scale.