AI Platform Engineer: DevOps, Observability & FinOps

EY; Pittsburgh (Allegheny County); On-site; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical & dental coverage

401(k) plan

Job summary

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. This role spans CI/CD pipelines, governance, cost visibility, and multi-environment runtimes, working with GPU inference and open telemetry to ensure secure, traceable, and economical AI workloads.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong collaboration with architects and leadership.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering.
• Hands-on CI/CD/CV pipelines and GitOps tooling experience.
• Hands-on expertise operating inference/model-serving frameworks (Ray Serve, vLLM, Triton, or NIM) on GPU infrastructure.
• Strong observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy or equivalent).
• Experience with cost management / FinOps tooling (OpenCost, Kubecost, or equivalent).
• 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: CI/CD/CV pipelines for ships AI services and runtime components.
• Own governance and discovery for AI assets and registries; experiment tracking and metadata.
• Own resource and cost management, including quotas and rate limits to keep AI execution bounded.
• Own the full observability stack: metrics, logs, traces, dashboards, and debugging tools.
• Own the OpenTelemetry collection layer, including multi-tenant receivers and Kafka sinks.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability using telemetry and cost signals to guide deployment decisions.
• Ensure cost and telemetry are identity-stamped per-tenant.

Skills

DevOps

MLOps

Observability

FinOps

Model governance

Cost management

GPU inference

OpenTelemetry

Education

Bachelor's degree in CS or related field

Master's degree in CS

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo

Jaeger

Envoy

Harbor

MLflow

Trivy

Kubecost

OpenCost

LangSmith

Langfuse

DCGM

Kubernetes

ArgoCD

Helm

GitHub Actions

GitLab CI

Job description

EY is seeking an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. This role spans CI/CD pipelines, governance, cost visibility, and multi-environment runtimes, working with GPU inference and open telemetry to ensure secure, traceable, and economical AI workloads.

The role sits at the intersection of DevOps, MLOps, FinOps, and observability, requiring strong collaboration with architects and leadership.