AI Platform Delivery & Observability Lead

EY; Baton Rouge (LA); On-site; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Total Rewards package

Medical and dental coverage

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll shape the runtime surface across cloud, on‑prem, edge, and air‑gapped environments, delivering repeatable AI workloads with cost controls and governance.

You’ll lead CI/CD/CV pipelines, model governance, and telemetry, while ensuring secure, compliant deployment and transparent operation to support diverse AI workloads at scale.

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.
• Strong hands-on DevOps experience with CI/CD/CV pipelines and GitOps tooling (ArgoCD, Helm, GitHub Actions/GitLab CI) for automated build, test, release, and rollback.
• 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) 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 CI/CD/CV pipelines that ship AI services, agents, and runtime components with automated build, test, verify, release, and rollback.
• Own governance and discovery for AI assets, including service catalog/registry, experiment tracking and model metadata, upstream registries/mirrors, CVE/SBOM scanning, lineage contracts, and license management.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization, so AI execution stays economically bounded and controllable per tenant and engagement.
• Own the full observability stack, including metrics, logs, traces, dashboards, LLM debugging/evaluation, and SLA/alert notifications.
• Own OpenTelemetry collection layer, including multi-tenant receiver, exporters and queues, GPU telemetry, and dynamic filtering.
• Automate GitOps-based delivery and continuous verification; embed quality, integrity, and cost gates into pipelines.
• Close the loop between delivery and observability by using telemetry, evaluation, and cost signals to drive deployment decisions, progressive rollout, and automated rollback.
• Ensure cost and telemetry are identity-stamped and per-tenant, so consumption and behavior are attributable end-to-end.

Skills

DevOps expertise

Observability

FinOps mindset

Communication

Multi-cloud/edge

Education

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

Tools

Prometheus

Grafana

Loki

Tempo/Jaeger

OpenTelemetry

Envoy

MLflow

Harbor

Trivy/SBOM

OpenLineage

Kubecost/OpenCost

Ray Serve

vLLM/Triton/NIM

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability for EY’s AI-native platform. You’ll shape the runtime surface across cloud, on‑prem, edge, and air‑gapped environments, delivering repeatable AI workloads with cost controls and governance.

You’ll lead CI/CD/CV pipelines, model governance, and telemetry, while ensuring secure, compliant deployment and transparent operation to support diverse AI workloads at scale.