AI Platform Delivery & Observability Lead

EY; Baton Rouge (LA); Presencial; USD 126 000 - 230 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Hybrid work model

Total Rewards package

Medical and dental coverage

Resumo da oferta

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.

Qualificações

• 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.

Responsabilidades

• 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.

Conhecimentos

DevOps expertise

Observability

FinOps mindset

Communication

Multi-cloud/edge

Formação académica

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

Ferramentas

Prometheus

Grafana

Loki

Tempo/Jaeger

OpenTelemetry

Envoy

MLflow

Harbor

Trivy/SBOM

OpenLineage

Kubecost/OpenCost

Ray Serve

vLLM/Triton/NIM

Descrição da oferta de emprego

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.