AI Platform Engineer — CI/CD, Observability & FinOps

Ernst & Young Oman; Austin (TX); Hybrid; USD 107,000 - 177,000; Full time

Benefits offered by this job

Hybrid work model

Medical and dental coverage

Paid time off

Job summary

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You will operate CI/CD/CV pipelines, govern AI assets, and ensure cost-aware governance while enabling scalable, compliant AI workloads.

The role blends DevOps, MLOps, and observability across cloud, on-prem, edge, and air-gapped environments, with strong emphasis on reproducibility, security, and cost transparency.

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, or equivalents).
• 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 and runtime components.
• Own governance and discovery for AI assets including registries, experiment tracking, and license management.
• Manage resource and cost attribution to keep AI execution economically bounded per tenant and engagement.
• Own the full observability stack: metrics, logs, traces, dashboards, and OpenTelemetry integration.
• Automate GitOps-based delivery and verification with policy gates in pipelines.
• Link delivery and observability to drive deployment decisions, progressive rollout, and rollback.

Skills

DevOps/MLOps mindset

CI/CD pipelines

GitOps tooling

Observability

Cost governance

Regulatory/compliance awareness

Education

Bachelor’s degree in Computer Science

Master’s degree in CS or related field

Tools

Ray Serve

vLLM

Triton

NIM

Prometheus

Grafana

Loki

Tempo/Jaeger

Envoy

MLflow

Trivy

OpenLineage

Kubecost/OpenCost

Job description

EY seeks an AI Systems Engineer to own delivery, model-serving, routing, and observability across EY’s AI-native platform. You will operate CI/CD/CV pipelines, govern AI assets, and ensure cost-aware governance while enabling scalable, compliant AI workloads.

The role blends DevOps, MLOps, and observability across cloud, on-prem, edge, and air-gapped environments, with strong emphasis on reproducibility, security, and cost transparency.