Senior AI Delivery Engineer – DevOps & Observability

EY; Jericho (NY); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid model

Medical and dental coverage

Pension and 401(k)

Paid time off

Flexible vacation policy

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform. You will build CI/CD pipelines, govern AI assets, and drive FinOps across cloud, on-prem, edge, and air-gapped environments.

In this role you’ll operate high-performance inference, implement open telemetry, and ensure repeatable, policy-compliant delivery across multi-tenant environments. The position supports a hybrid work model in the US.

Qualifications

• 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, including 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, 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

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines that ship AI services, agents, 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, including metrics, logs, traces, dashboards, LLM debugging and evaluation, and SLA/alert notifications.
• Own the OpenTelemetry collection layer, including multi-tenant receiver, exporters and queues, DCGM exporter for GPU telemetry, processor batching, 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 and cost signals to drive deployment decisions and automated rollback.
• Ensure cost and telemetry are identity-stamped and per-tenant, so consumption is attributable end-to-end.

Skills

DevOps

MLOps

Observability

FinOps

OpenTelemetry

Model serving

Cost attribution

Hybrid cloud

Communication

Education

Bachelor’s degree in Computer Science or related field

Tools

Ray Serve

vLLM

Triton

NIM

Envoy

Prometheus

Grafana

Loki

Tempo

Jaeger

MLflow

Trivy

Harbor

Kubecost

OpenLineage

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability of EY’s AI-native platform. You will build CI/CD pipelines, govern AI assets, and drive FinOps across cloud, on-prem, edge, and air-gapped environments.

In this role you’ll operate high-performance inference, implement open telemetry, and ensure repeatable, policy-compliant delivery across multi-tenant environments. The position supports a hybrid work model in the US.