AI DevOps & Observability Architect

EY; Trenton (NJ); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k) plans

Generous paid time off

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You’ll build CI/CD pipelines, govern AI assets, and ensure cost-aware, auditable execution in cloud, on-prem, and edge environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on experience with GPU inference, OpenTelemetry, and scalable delivery pipelines. Hybrid work is available.

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field
• 8+ years in DevOps, MLOps, platform, or observability engineering with 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 on GPU infrastructure
• Strong observability experience with OpenTelemetry
• Experience with API gateways and request routing
• Experience with FinOps tooling and quota enforcement
• Familiarity with model/artifact registries and lineage tracking
• Proven track record operating AI or service infrastructure under compliance and regulatory constraints

Responsibilities

• Own DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines delivering AI services and runtime components
• Own governance and discovery for AI assets and registries, model metadata, and license management
• Own resource and cost management including quotas and attribution to keep AI execution bounded
• Own the full observability stack: metrics, logs, traces, dashboards, and LLM debugging
• Own the OpenTelemetry collection layer and ensure reliable signal routing
• Automate GitOps-based delivery and verification with policy gates
• Close the loop between delivery and observability using telemetry and cost signals for deployment decisions
• Ensure per-tenant identity stamping for consumption and telemetry alignment

Skills

DevOps for AI workloads

MLOps

Observability

FinOps

OpenTelemetry

GPU inference

CI/CD pipelines

GitOps

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You’ll build CI/CD pipelines, govern AI assets, and ensure cost-aware, auditable execution in cloud, on-prem, and edge environments.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring hands-on experience with GPU inference, OpenTelemetry, and scalable delivery pipelines. Hybrid work is available.