• Design and implement core backend systems and integrations that power the product.
• core backend systems
• integrations
• Design and build our data platform (orchestration, pipelines, developer workflows)
• data platform
• Create scalable systems for data ingestion, transformation, and access
• data ingestion, transformation, and access
• Design data models and APIs that won’t collapse under growth.
• data models and APIs
• Make sane decisions about schemas, indexes, migrations, and performance.
• Own infrastructure for data + AI workloads (containers, orchestration, cloud services)
• infrastructure for data + AI workloads
• Enable self-serve data workflows for engineering and product teams
• self-serve data workflows
• Improve observability, reliability, and performance across the data stack
• observability, reliability, and performance
• Support AI/ML systems (embeddings, vector data, model pipelines)
• AI/ML systems
• Build tooling for document processing, metadata, and normalization
• document processing, metadata, and normalization