AI Platform Delivery & Observability Manager

Ernst & Young Oman; Honolulu (HI); Hybrid; USD 126,000 - 230,000; Full time

Benefits offered by this job

Hybrid work model

Flexible vacation policy

Job summary

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will build CI/CD pipelines, governance, and cost visibility across cloud, on-prem, edge, and air-gapped environments.

This role integrates DevOps, MLOps, FinOps, and observability, delivering secure model execution and repeatable AI workloads with measurable telemetry and governance. Hybrid work and global collaboration are expected.

Qualifications

• 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, including CI/CD/CV pipelines and GitOps tooling for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong experience with observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing, including streaming responses.
• Experience with cost management / FinOps tooling and quota/rate-limit enforcement.
• Familiarity with model/artifact registries and supply-chain scanning.
• 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

• Own DevOps and delivery for AI workloads: build and operate the CI/CD/CV pipelines that ship AI services, agents, and runtime components, including automated build, test, continuous verification, 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.
• Own the full observability stack, including metrics, logs, traces, dashboards, and SLA/alert notifications.
• Own the OpenTelemetry collection layer, including multi-tenant receiver, exporters and queues, processor batching, and dynamic filtering.
• Automate GitOps-based delivery and continuous verification; embedding quality, integrity, and cost gates into pipelines so releases are policy-compliant by default.
• Close the loop between delivery and observability by using telemetry, evaluation, 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

CI/CD pipelines

GitOps

OpenTelemetry

Observability

DevOps

Cost attribution

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

LangSmith

Langfuse

Prometheus

Grafana

Jaeger

Job description

EY seeks an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will build CI/CD pipelines, governance, and cost visibility across cloud, on-prem, edge, and air-gapped environments.

This role integrates DevOps, MLOps, FinOps, and observability, delivering secure model execution and repeatable AI workloads with measurable telemetry and governance. Hybrid work and global collaboration are expected.