AI Systems Engineer & DevOps Observability Lead

EY; Indianapolis (IN); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Medical and dental coverage

Pension and 401(k) plans

Paid time off options

Hybrid work model

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layers of EY’s AI-native platform. You will manage CI/CD/CV pipelines, governance for AI assets, and cost-aware deployment across cloud, on‑prem, edge, and air‑gapped environments.

You will operate inference frameworks on GPUs, build deep observability, and implement policy-driven releases in a multi-tenant, regulated setting while collaborating with engineers, architects, and leadership.

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 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 experience with observability stacks and OpenTelemetry.
• Experience with API gateways and request routing, including streaming responses.
• Experience with cost management / FinOps tooling and quota enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.
• Proven track record operating AI infrastructure under regulated constraints.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines, automated build, test, release and rollback.
• Own governance and discovery for AI assets and model metadata.
• Own resource and cost management with quota and attribution.
• Own the full observability stack: metrics, logs, traces, dashboards.
• Own OpenTelemetry collection layer for multi-tenant signals.
• Automate GitOps-based delivery and policy-compliant releases.
• Close the loop between delivery and observability to inform deployment decisions.
• Ensure identity-stamped telemetry and per-tenant cost accounting.

Skills

DevOps expertise

MLOps / platform engineering

Observability (OpenTelemetry)

FinOps / cost attribution

Model governance & registries

Multi-environment (cloud/on-prem/edge)

Clear communication

Education

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

Tools

Ray Serve

vLLM/Triton/NIM

Envoy

Prometheus/Grafana/Loki

LangSmith/Langfuse

Harbor/MLflow/Trivy

ArgoCD/Helm/GitHub Actions

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layers of EY’s AI-native platform. You will manage CI/CD/CV pipelines, governance for AI assets, and cost-aware deployment across cloud, on‑prem, edge, and air‑gapped environments.

You will operate inference frameworks on GPUs, build deep observability, and implement policy-driven releases in a multi-tenant, regulated setting while collaborating with engineers, architects, and leadership.