AI-Powered Candidate Screening & Evaluation Workflow
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This n8n workflow automates the initial screening and evaluation of job applicants by leveraging AI. It gathers candidate data from various platforms like LinkedIn, GitHub, and LeetCode, and uses large language models to provide structured evaluations, significantly streamlining your hiring process.
About This Workflow
Revolutionize your recruitment pipeline with this AI-driven workflow. Upon receiving a new job application via JotForm, this system automatically extracts key candidate information, including their LinkedIn profile, GitHub activity, LeetCode statistics, and resume. It then dispatches this data to a series of specialized AI agents powered by OpenRouter Chat Models. These agents conduct in-depth, multi-faceted evaluations, assessing candidates based on their professional presence, coding skills, and project contributions. The output is a structured, comprehensive candidate report, preparing data for seamless integration into your HR spreadsheets or ATS.
Key Features
- Automated Application Intake: Instantly process new job applications submitted through JotForm.
- Multi-Platform Data Scraping: Automatically fetch candidate details from LinkedIn profiles, GitHub repositories, and LeetCode statistics.
- AI-Powered Candidate Evaluation: Utilize specialized Langchain agents and OpenRouter LLMs for intelligent evaluation of resumes, LinkedIn presence, GitHub contributions, and LeetCode performance.
- Structured Output: Receive AI evaluation results in a clear, parseable format for easy analysis and integration.
- Streamlined HR Operations: Reduce manual screening effort and accelerate the initial stages of the hiring process.
How To Use
- Configure JotForm Trigger: Connect your JotForm account and select the form used for job applications to initiate the workflow.
- Set Up HTTP Request Nodes: Provide necessary API keys or authentication for scraping data from LinkedIn, GitHub, and LeetCode.
- Integrate OpenRouter Credentials: Ensure your OpenRouter Chat Model nodes are configured with valid API keys for AI processing.
- Customize AI Agent Prompts: (Optional) Adjust the
parametersof thelangchain.agentnodes (linkedin evaluation,github evaluation,leetcode evaluation,resume evaluation) to fine-tune evaluation criteria and output format. - Review Output Parsers: Verify the
Structured Output Parsernodes are correctly configured to extract the desired insights from the AI evaluations.
Apps Used
Workflow JSON
{
"id": "55956683-f247-4994-8c00-1334b8544e7b",
"name": "AI-Powered Candidate Screening & Evaluation Workflow",
"nodes": 12,
"category": "Operations",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 55956683-f247...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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