recruiting · saas · workflow
Building LinkedIn's Hiring Assistant: an agentic AI for recruiter sourcing, evaluation, and engagement at global scale
Candidate sourcing and evaluation are the most resource-intensive parts of recruiting, combining high-value decision-making with large volumes of repetitive pattern-recognition tasks that require human micromanagement to keep pipelines updated.
How it works
Common implementation structure
How this type of workflow is generally built, generalized across documented cases — not tied to any one vendor's stack. Click any stage to read what happens there. Specific products that implement these stages appear in “Tools commonly seen” below.
Stage 1 · Recruiter initiates request
The interactive interface allows recruiters to converse directly with Hiring Assistant to clarify hiring requirements and align on expectations.
Tools used
LinkedIn Recruiter SearchRecommended MatchesEconomic GraphLinkedIn Talent InsightsGraphQL API
Outcome
Hiring Assistant reached global availability, enabling sourcing across 1.2+ billion profiles with enterprise-grade throughput and evaluating candidates in seconds via custom fine-tuned LLMs, freeing recruiters to focus on high-value work.
What failed first
A simple ReAct-style architecture was found insufficient for enterprise-grade recruiting: LLMs did not follow instructions reliably, produced hallucinations, and complex reasoning introduced unacceptable latency.
Results
Volume1.2+ billion profiles
Grounding & classification
Source type: technical build writeup
32 fields verified against source quotes.
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