AI Systems Engineer: DevOps, Observability & FinOps

Ernst & Young Oman; McLean (VA); 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 is seeking an AI Systems Engineer to own the delivery, model-serving, routing, and observability layer of EY’s AI-native platform. You will manage CI/CD pipelines, governance, and cost visibility across cloud, on-prem, edge, and air-gapped environments.

You’ll work across DevOps, MLOps, FinOps, and observability disciplines to ensure secure, compliant AI workloads with transparent telemetry and governance. Hybrid work model offered.

Qualifications

• 8+ years in DevOps, MLOps, platform, or observability engineering with hands-on ownership of AI or high-throughput services.
• Hands-on DevOps experience with CI/CD pipelines and GitOps tooling for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong observability stacks (Prometheus, Grafana, Loki, Tempo/Jaeger) and OpenTelemetry.
• Experience with API gateways and request routing (Envoy) including streaming responses.
• Experience with 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

• Supports DevOps and delivery for AI workloads: build and operate the CI/CD/CV pipelines that ship AI services and runtime components.
• Own governance and discovery for AI assets, including registries and license management.
• Own resource and cost management, including quotas and rate limits.
• Own the full observability stack: metrics, logs, traces, dashboards, and SLA/alerting.
• Own the OpenTelemetry collection layer for reliable signal capture.
• Automate GitOps-based delivery and continuous verification with policy gates.
• Close the loop between delivery and observability to drive deployment decisions and automated rollback.
• Ensure cost and telemetry are per-tenant and attributable end-to-end.

Skills

DevOps

MLOps

Observability

FinOps

Model governance

Cross-team collaboration

Education

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

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

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. You will manage CI/CD pipelines, governance, and cost visibility across cloud, on-prem, edge, and air-gapped environments.

You’ll work across DevOps, MLOps, FinOps, and observability disciplines to ensure secure, compliant AI workloads with transparent telemetry and governance. Hybrid work model offered.