AI Platform Engineer — DevOps, Observability & FinOps Lead

EY; Buffalo (NY); Remote; USD 150,000 - 235,000; Full time

Benefits offered by this job

Hybrid/Remote work options

Total Rewards package

Paid time off options

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage pipelines, governance, cost attribution, and multi-environment runtimes across cloud, on-prem, edge, and air-gapped setups.

The role blends DevOps, MLOps, FinOps, and observability, requiring experience with GPUs, model-serving frameworks, and OpenTelemetry. Join a team enabling compliant, scalable AI workloads.

Qualifications

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

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets, including registries and model metadata.
• Own resource and cost management, including quotas and attribution per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA notifications.
• Own the OpenTelemetry collection layer for reliable signal capture.
• Automate GitOps-based delivery with policy gates in pipelines.
• Close the loop between delivery and observability for deployment decisions and automatic rollbacks.
• Ensure cost and telemetry are identity-stamped and per-tenant.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Multi-environment

Education

CS degree

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

OpenTelemetry

Envoy

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll manage pipelines, governance, cost attribution, and multi-environment runtimes across cloud, on-prem, edge, and air-gapped setups.

The role blends DevOps, MLOps, FinOps, and observability, requiring experience with GPUs, model-serving frameworks, and OpenTelemetry. Join a team enabling compliant, scalable AI workloads.