AI Platform Engineer

Your Role:

• Design and build a scalable data and AI platform supporting batch and streaming workloads.
• Establish standardized infrastructure, frameworks, and best practices for data and AI workloads.
• Build and manage orchestration frameworks such as Airflow, Prefect, or Dagster, including reusable pipeline templates.
• Enable self-service data access through APIs, query engines, and semantic layers.
• Develop infrastructure to support AI/ML training, experimentation, deployment, reproducibility, and model versioning.
• Implement platform-wide logging, monitoring, alerting, governance, security, and access controls.
• Define and maintain SLAs for platform services and data pipelines.
• Standardize datasets as discoverable, documented, versioned, and reusable data products.
• Build internal platform capabilities and tooling that improve developer experience and engineering productivity.
• Design systems that scale with increasing data volumes and concurrent workloads without frequent re-architecture.
• Collaborate with engineering, data, and business teams to align platform capabilities with business and data use cases.

To Succeed, You Will Need: