What API and data model would support a new Feed workflow for hiring managers at global scale

Problem Statement Description

Product context: LinkedIn is Microsoft's professional network; its products include profiles, feed, jobs, recruiting, LinkedIn Learning, sales tools, messaging, and ads.

LinkedIn is exploring a new Feed workflow tailored to hiring managers who need to stay informed about talent, roles, recruiting activity, market signals, and team hiring priorities. Unlike a general professional feed, this experience may need to combine social updates, candidate signals, recruiter collaboration, job requisition context, skills intelligence, and company-specific hiring workflows in a trusted, privacy-safe way.

You are asked to define the API and data model that would support this workflow at global scale. The focus is not on designing the UI or ranking algorithm in detail, but on identifying the core entities, relationships, read/write flows, integration points, permissions, and system behaviors required to make the feed useful, reliable, extensible, and compliant across regions and customer types.

Assume the product must work for hiring managers across small businesses, large enterprises, multiple geographies, and different recruiting setups. It may need to interoperate with LinkedIn identity, jobs, recruiter tools, applicant data, skills data, notifications, and external HR systems, while maintaining strong privacy, security, and professional trust.

The experience should consider:

- The primary hiring manager workflows the Feed must support, such as reviewing candidate activity, tracking open roles, collaborating with recruiters, and acting on hiring insights.

- Core data entities and relationships, including members, companies, roles, requisitions, candidates, recruiters, feed items, actions, comments, permissions, and audit history.

- API surface area for creating, reading, updating, filtering, ranking, acknowledging, and acting on feed items across web, mobile, and partner integrations.

- Data freshness, pagination, idempotency, consistency, localization, and scale requirements for a global professional network.

- Permissioning and privacy boundaries between hiring managers, recruiters, candidates, companies, and external applicant tracking or HR systems.

- Reliability, observability, error handling, abuse prevention, compliance, and data retention expectations.

- Product trade-offs between real-time updates and digestible summaries, standardized feed objects and extensible domain-specific payloads, and internal-only versus partner-facing APIs.

Your goal is to frame a technically sound product architecture that enables a high-trust hiring manager Feed without overbuilding. Clarify assumptions, define the minimum durable data model and API capabilities, identify key risks and dependencies, and explain how the design would evolve as the workflow scales across LinkedIn’s hiring ecosystem.