Senior AI Systems Engineer: DevOps, Observability & FinOps

Ernst & Young Oman; Oklahoma City (OK); Hybrid; USD 107,000 - 177,000; Full time

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. This role bridges DevOps, MLOps, FinOps, and observability across cloud, on-prem, edge, and air-gapped environments.

You will own CI/CD/CV pipelines, governance for AI assets, cost attribution per tenant, and a complete observability stack. Strong focus on scalable delivery and repeatable, auditable AI workloads.

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 for automated build, test, release, and rollback.
• Hands-on expertise operating inference/model-serving frameworks on GPU infrastructure.
• Strong experience with observability stacks 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

• Supports DevOps and delivery for AI workloads: build and operate CI/CD/CV pipelines shipping AI services and runtime components.
• Own governance and discovery for AI assets including registries, experiment tracking, and metadata tooling.
• Own resource and cost management including quotas and cost attribution to keep AI execution economical.
• Own the full observability stack: metrics, logs, traces, dashboards, and model debugging tools.
• Own the OpenTelemetry collection layer and ensure reliable signal capture and routing.
• Automate GitOps-based delivery and verification; embed quality, integrity, and cost gates into pipelines.
• Close the loop between delivery and observability using telemetry and cost signals to drive deployments.
• Ensure cost and telemetry are identity-stamped and per-tenant for accountable consumption.

Skills

DevOps

MLOps

Observability

FinOps

Governance

Multi-env

Communication

Education

Bachelor’s in CS or related field

Tools

ArgoCD

Helm

GitHub Actions

GitLab CI

Ray Serve

vLLM

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. This role bridges DevOps, MLOps, FinOps, and observability across cloud, on-prem, edge, and air-gapped environments.

You will own CI/CD/CV pipelines, governance for AI assets, cost attribution per tenant, and a complete observability stack. Strong focus on scalable delivery and repeatable, auditable AI workloads.