AI Systems Engineer: DevOps & Observability

EY; Greenville (SC); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Paid time off

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. The role sits at the intersection of DevOps, MLOps, FinOps, and observability, delivering repeatable, secure AI workloads.

The ideal candidate will design automated delivery pipelines, operate high‑performance inference, and build deep observability and cost visibility while complying with regulatory constraints.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Strong hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI).
• Hands-on expertise with 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 (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 that ship AI services and runtime components, including automated build, test, verification, release, and rollback.
• Own governance and discovery for AI assets, including service catalogs/registries and model metadata tracking.
• Own resource and cost management, with quotas and rate limits to keep AI execution economically bounded per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging/evaluation tools.
• Own the OpenTelemetry collection layer and multi-tenant signals routing for reliable signal capture.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollbacks.
• Ensure cost and telemetry are identity-stamped and per-tenant for FinOps accountability.

Skills

DevOps

MLOps

Observability

GPU inference

OpenTelemetry

Cost governance

API gateways

GitOps

LangSmith/Langfuse

Education

Bachelor's degree in Computer Science or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM/Triton/NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Envoy

OpenCost/Kubecost

Harbor/MLflow

Trivy

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform across cloud, on‑prem, edge, and air‑gapped environments. The role sits at the intersection of DevOps, MLOps, FinOps, and observability, delivering repeatable, secure AI workloads.

The ideal candidate will design automated delivery pipelines, operate high‑performance inference, and build deep observability and cost visibility while complying with regulatory constraints.