Driving data enhancement & recruitment success with LinkedIn’s unified integrations

This post details the engineering effort behind LinkedIn's unified integrations platform for hiring data. It elaborates on the BuildIn (partner-push) and BuildOut (LinkedIn-owned pull/push) integration models, highlighting challenges like semantic variability, entity interdependency, and operational scale. Key design principles include security, isolation, observability, unified data contracts, and idempotent, replayable, and evolvable data paths. The architecture features gateway adapters for BuildIn and BuildOut, a centralized integration core, and leverages Temporal for workflow orchestration and Kafka for streaming. Specific technical contributions include the development of smart throttling for quota-aware freshness control within the BuildOut framework's Data Manager, and the use of Temporal for orchestrating long-running, dependency-aware workflows with guaranteed retries and deterministic recovery. The post also emphasizes the importance of these integrations for grounding AI agents in unified enterprise context.