Senior AI Platform Engineer: Delivery & Observability

EY; Secaucus (NJ); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Flexible vacation policy

Medical & dental coverage

Pension and 401(k)

Paid time off

Job summary

EY invites you to join as an AI Systems Engineer responsible for the delivery, model-serving, routing and observability of EY’s AI-native platform across cloud, on-prem, edge and air-gapped environments.

You will operate at the intersection of DevOps, MLOps, FinOps and observability, building CI/CD pipelines, governance, cost visibility, and end-to-end traceability for scalable AI workloads.

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).
• 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

• 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, model metadata, and upstream registries/mirrors.
• Own resource and cost management, including quotas and rate limits, cost attribution and utilization.
• Own the full observability stack: metrics, logs, traces, dashboards, and AI debugging/evaluation tools.
• Own the OpenTelemetry collection layer, including multi-tenant receiver and exporters.
• Automate GitOps-based delivery and continuous verification with policy-based gates.
• Close the loop between delivery and observability using telemetry and cost signals to drive decisions.
• Ensure cost and telemetry are identity-stamped and per-tenant, linking FinOps to workloads.

Skills

DevOps expertise

Observability

FinOps mindset

Model governance familiarity

Cloud/on-prem/edge

Communication skills

Education

Bachelor's or Master’s in CS or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Jaeger

OpenTelemetry

LangSmith

Langfuse

Job description

EY invites you to join as an AI Systems Engineer responsible for the delivery, model-serving, routing and observability of EY’s AI-native platform across cloud, on-prem, edge and air-gapped environments.

You will operate at the intersection of DevOps, MLOps, FinOps and observability, building CI/CD pipelines, governance, cost visibility, and end-to-end traceability for scalable AI workloads.