AI Systems Engineer & DevOps Observability Lead

EY; McLean (VA); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

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 manage CI/CD pipelines, governance, cost attribution, and multi-environment runtimes for regulated workloads.

You’ll operate GPU-based inference, OpenTelemetry collection, and end-to-end telemetry, enabling repeatable, auditable AI workloads with strong GitOps practices. Hybrid in US, with competitive compensation.

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: build and operate the CI/CD/CV pipelines for AI services and runtime components.
• Own governance and discovery for AI assets, including service catalog/registry, experiment tracking, and model metadata.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA/alert notifications.
• Own the OpenTelemetry collection layer for multi-tenant environments.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure cost and telemetry are identity-stamped and per-tenant for FinOps traceability.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Cloud

OpenTelemetry

API gateways

GPU inference

GitOps

CI/CD

Education

Bachelor’s or Master’s degree

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

LangSmith

Langfuse

Envoy

Harbor

MLflow

Trivy

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 manage CI/CD pipelines, governance, cost attribution, and multi-environment runtimes for regulated workloads.

You’ll operate GPU-based inference, OpenTelemetry collection, and end-to-end telemetry, enabling repeatable, auditable AI workloads with strong GitOps practices. Hybrid in US, with competitive compensation.