AI Systems Engineer & DevOps - Observability & FinOps

EY; Alpharetta (GA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Medical coverage

Dental coverage

401(k)

Paid time off

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model‑serving, routing, and observability layer of EY’s AI‑native platform. You will ship, run, and observe AI workloads across cloud, on‑prem, edge, and air‑gapped environments.

The role combines DevOps, MLOps, FinOps, and observability, requiring hands‑on experience with CI/CD pipelines, GPU inference, and advanced telemetry. EY offers hybrid work and broad Total Rewards beyond base pay.

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, 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), including streaming responses.
• Experience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent) 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 and GitOps for AI services and runtime components.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management, including quotas and attribution.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
• Own the OpenTelemetry collection layer for multi‑tenant, reliable signal capture.
• Automate GitOps delivery and verification with quality and cost 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.

Skills

DevOps

MLOps

Observability

FinOps

OpenTelemetry

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

ArgoCD

Helm

GitHub Actions/GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

LangSmith

Langfuse

OpenLineage

Harbor

MLflow

Trivy

SBOM

Kubecost

OpenCost

Job description

EY is seeking an AI Systems Engineer to own the delivery, model‑serving, routing, and observability layer of EY’s AI‑native platform. You will ship, run, and observe AI workloads across cloud, on‑prem, edge, and air‑gapped environments.

The role combines DevOps, MLOps, FinOps, and observability, requiring hands‑on experience with CI/CD pipelines, GPU inference, and advanced telemetry. EY offers hybrid work and broad Total Rewards beyond base pay.