AI Systems Engineer: DevOps, Observability & AI Delivery

EY; Hartford (CT); On-site; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid/remote work flexibility

Total Rewards package

Paid time off

Job summary

EY seeks an AI Systems Engineer to own delivery, model serving, routing, and observability for EY’s AI-native platform. You will shape how AI services are built, deployed, and observed across cloud, on‑prem, edge, and air-gapped environments, collaborating with senior engineers to test and advance capabilities.

The role bridges DevOps, MLOps, FinOps, and observability, requiring deep expertise in pipelines, GPU inference, model governance, and multi-tenant cost control.

Qualifications

• 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).
• 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

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets, including registries, model metadata, and license management.
• Own resource and cost management with quotas and attribution to keep AI execution economical.
• Own the full observability stack: metrics, logs, traces, dashboards, and evaluation tooling.
• Own OpenTelemetry collection, including multi-tenant receivers and exporters for reliable signal routing.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability to guide deployment decisions and rollbacks.
• Ensure identity-stamped, per-tenant telemetry and cost signals for FinOps integration.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Multi-cloud

Communication

Education

Bachelor’s or Master’s degree in CS

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

OpenTelemetry

Job description

EY seeks an AI Systems Engineer to own delivery, model serving, routing, and observability for EY’s AI-native platform. You will shape how AI services are built, deployed, and observed across cloud, on‑prem, edge, and air-gapped environments, collaborating with senior engineers to test and advance capabilities.

The role bridges DevOps, MLOps, FinOps, and observability, requiring deep expertise in pipelines, GPU inference, model governance, and multi-tenant cost control.