Senior AI Platform Engineer – Delivery & Observability

EY; Trenton (NJ); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will shape how AI services are built, deployed, and governed across cloud, on-prem, edge, and air-gapped environments, ensuring repeatable delivery and cost control.

You will work across DevOps, MLOps, FinOps, and observability, building pipelines, securing model execution, and driving progressive rollout with telemetry-driven decisions.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on production ownership of AI or high-throughput services.
• Hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Experience operating inference/model-serving frameworks on GPU infrastructure.
• Strong observability experience with metrics, logs, traces, and OpenTelemetry.
• Experience with API gateways and request routing, including streaming responses.
• Familiarity with cost management / FinOps tooling and quota enforcement.
• Knowledge of model/artifact registries and governance tools.
• Proven track record delivering AI/service infrastructure under compliance constraints.

Responsibilities

• Supports DevOps and delivery for AI workloads by building and operating CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets including registries and model metadata.
• Own resource and cost management including quotas, rate limits, and cost attribution.
• Own the full observability stack: metrics, logs, traces, dashboards, and LLm evaluation tooling.
• Own the OpenTelemetry collection layer and GPU telemetry for reliable signal routing.
• Automate GitOps-based delivery and verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure cost and telemetry are per-tenant and attributable end-to-end.

Skills

DevOps

MLOps

Observability

OpenTelemetry

Cost governance

GPU inference

Multi-cloud

GitOps

Education

Bachelor's or Master's in Computer Science or related field

Tools

Ray Serve

vLLM

Triton

NIM

Envoy

Prometheus

Grafana

Loki

Tempo/Jaeger

LangSmith

Langfuse

Harbor

MLflow

Trivy

OpenLineage

Job description

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will shape how AI services are built, deployed, and governed across cloud, on-prem, edge, and air-gapped environments, ensuring repeatable delivery and cost control.

You will work across DevOps, MLOps, FinOps, and observability, building pipelines, securing model execution, and driving progressive rollout with telemetry-driven decisions.