The AI Systems Engineer - DevOps & Observability Manager at EY is responsible for managing the delivery, model-serving, routing, and observability layer of EY's AI-native platform. This role focuses on ensuring that AI workloads are delivered safely and efficiently across various environments, including cloud and on-premises. The engineer will work at the intersection of DevOps, MLOps, FinOps, and observability, making it essential to have a strong understanding of automated delivery pipelines and high-performance inference systems. The position requires a combination of technical expertise and effective communication skills to collaborate with various teams.

• Bachelor's or Master's degree in Computer Science or a related technical field.
• 8+ years of experience in DevOps, MLOps, platform, or observability engineering.
• Strong hands-on experience with CI/CD/CV pipelines and GitOps tooling.
• Expertise in operating inference/model-serving frameworks on GPU infrastructure.
• Experience with observability stacks and OpenTelemetry.
• Familiarity with cost management and FinOps tooling.

• Own DevOps and delivery for AI workloads by building and operating CI/CD/CV pipelines.
• Manage governance and discovery for AI assets, including service catalog and experiment tracking.
• Oversee resource and cost management to ensure AI execution remains economically bounded.
• Implement the full observability stack, including metrics, logs, and traces.
• Automate GitOps-based delivery and continuous verification to ensure policy compliance.
• Utilize telemetry and cost signals to drive deployment decisions and automated rollback.

• Ernst & Young (EY) offers a comprehensive and competitive benefits package designed to support the well-being of its employees across various dimensions.