AI Platform DevOps & Observability Lead

EY; Irvine (CA); Hybrid; USD 151,000 - 262,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Pension and 401(k)

Flexible vacation policy

Job summary

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform across cloud, on-prem, edge, and air-gapped environments. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, balancing automated delivery with cost and governance in regulated contexts.

The ideal candidate will design and operate CI/CD/CV pipelines, build scalable inference systems on GPUs, and drive end-to-end telemetry and cost

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 8+ years in DevOps, MLOps, platform, or observability engineering with ownership of AI or high-throughput services.
• Hands-on DevOps experience with 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, NIM) on GPU infrastructure.
• Strong observability experience (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy).
• Experience with cost management tools (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/service infrastructure under compliance, security, or regulatory constraints.
• Ability to define ownership boundaries and consumption contracts with platform, trust, and data teams.

Responsibilities

• Own DevOps and delivery for AI workloads: CI/CD/CV pipelines, release and rollback for AI services and runtimes.
• Own governance and discovery for AI assets, including registries and model metadata.
• Own resource and cost management with quotas and cost attribution per tenant.
• Own the full observability stack: metrics, logs, traces, dashboards, and LangSmith/Langfuse for evaluation.
• Own the OpenTelemetry collection layer across multi-tenant environments.
• Automate GitOps-based delivery with policy-based gates into pipelines.
• Integrate telemetry, evaluation, and cost signals to drive deployment decisions and automated rollbacks.
• Ensure identity-stamped cost and telemetry per tenant across workloads.

Skills

CI/CD/CV pipeline design

Model-serving frameworks

Observability

FinOps mindset

Governance and registries

Multi-env operation

Communication

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Artifactory/Nexus/Harbor

MLflow

Trivy

OpenLineage

Prometheus/Grafana/Loki/Tempo/Jaeger

Envoy

Job description

EY is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform across cloud, on-prem, edge, and air-gapped environments. This role sits at the intersection of DevOps, MLOps, FinOps, and observability, balancing automated delivery with cost and governance in regulated contexts.

The ideal candidate will design and operate CI/CD/CV pipelines, build scalable inference systems on GPUs, and drive end-to-end telemetry and cost