AI Systems Delivery & Observability Lead

EY; Palo Alto (CA); Remote; USD 126,000 - 230,000; Full time

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s 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.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, ensuring repeatable, economical AI workloads with strong telemetry and governance.

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.
• Hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• 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), including streaming responses.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost) 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

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines to ship AI services and runtime components.
• Own governance and discovery for AI assets: registries, experiment tracking, metadata, and licenses.
• Own resource and cost management: quotas, rate limits, cost attribution to tenants.
• Own the full observability stack: metrics, logs, traces, dashboards, and evaluation tooling.
• Own OpenTelemetry collection layer for multi-tenant signals and GPU telemetry.
• Automate GitOps-based delivery and verification with policy gates.
• Close the loop between delivery and observability to drive deployments and rollbacks.
• Ensure cost and telemetry are identity-stamped and per-tenant for accountable usage.

Skills

DevOps

MLOps

Observability

FinOps

Model governance

OpenTelemetry

AI workloads delivery

Platform ownership

Education

Bachelor’s or Master’s in CS or related field

Tools

Ray Serve

vLLM

Triton

NIM

Envoy

OpenTelemetry

Prometheus

Grafana

Loki

Jaeger

LangSmith

Langfuse

MLflow

Trivy

Harbor

OpenLineage

Kubecost/OpenCost

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s 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.

This role sits at the intersection of DevOps, MLOps, FinOps, and observability, ensuring repeatable, economical AI workloads with strong telemetry and governance.