👥 AI recruiting pipeline: Job to candidate shortlist with Apollo & Airtable

⚡ 1,356 views · 👥 HR & Recruitment

💡 Pro Tip — If you’re pulling LinkedIn data through HTTP requests or dealing with API restrictions, there’s a community node called ScraperNode that handles this natively. It has dedicated scrapers for profiles, companies, jobs, and people search — you just pass a URL and get structured data back.

Description

Who’s it for

Recruiting agencies, executive search firms, and in-house talent teams that want to automate candidate sourcing and prequalification. Instead of spending hours searching, scoring, and writing outreach, this workflow turns any job description into a ready-to-use shortlist with personalized messages.

Youtube Walkthrough

What it does (How it works)

This workflow takes a job description (title, description, and location) and runs a complete recruiting automation pipeline:

• Normalize job titles and generate variations to widen search coverage.
• Search candidates in Apollo (or your CRM / database of choice).
• Remove duplicates to keep clean lists.
• Score candidates with AI (0–5) and provide concise reasoning across experience, industry, and seniority.
• Enrich LinkedIn profiles (name, title, image, location, experience).
• Create structured candidate assessments (summary, alignment, red flags, positives).
• Generate outreach messages (email + LinkedIn DM) tailored to the candidate.
• Write to Airtable for job/candidate tracking and downstream automation.

Everything is plug-and-play, with no manual searching or copy-pasting required.

Requirements

• n8n (Cloud or self-hosted)
• Airtable account + API access
• Apollo API or your preferred candidate source
• LLM provider: OpenAI or Anthropic
• LinkedIn enrichment API (RapidAPI, Apify, etc.)

> ⚠️ Do not hardcode API keys in HTTP nodes. Always use Credentials in n8n.

Airtable table specifications

Create one base (e.g., Candidate Search – From Job Description) with two tables:

Jobs Table

• Job Title (text)
• Job Description (long text)
• Job Location (text)
• Candidates (linked to Candidates table)

Candidates Table

• Core fields: Name, LinkedIn URL, Job Title, Location, Image URL, Job Searches (linked)
• Assessment fields: Summary Fit Score, Executive Summary, Title Alignment, Skill Alignment, Industry Alignment, Seniority Alignment, Company Type Alignment, Educational Alignment, Potential Red Flags, Positive Signals, Final Recommendation, Next Steps Suggestion
• Outreach fields: Email Subject, Email Body, LinkedIn Message

How to set up

1. Connect credentials
   Add Airtable, Apollo/CRM, and OpenAI/Anthropic credentials under n8n Credentials.

2. Create Airtable base/tables
   Follow the above spec for Jobs and Candidates. Match field names exactly to avoid mapping errors.

3. Configure the trigger
   The workflow starts from a Form/Webhook node. It captures:

   • Job Title (required)
   • Job Description (required)
   • Location (required)
   • Target Companies (optional, comma-separated domains)

4. Job title mutation
   The workflow uses an AI node to normalize the job title and generate up to 5 variations for broader candidate searches.

5. Candidate search
   Apollo (or your CRM API) is queried with the generated titles and location filters. Results are deduped.

6. AI scoring & structuring
   Candidates are scored 0–5 with clear reasoning (experience, industry, seniority, general fit). Profiles are formatted into structured JSON for Airtable.

7. LinkedIn enrichment
   Enrichment API fetches missing data (geo, image, job history).

8. Candidate assessment
   An AI model produces a full recruiter-ready evaluation (fit summary, strengths, red flags).

9. Outreach generation
   The workflow drafts a concise cold email (<75 words) and LinkedIn DM (<60 words), consultative in tone.

10. Write to Airtable
    All jobs and candidates (with assessments and outreach messages) are logged for review and integration.

How to customize

• Swap Apollo with your CRM (Greenhouse, Bullhorn, etc.).
• Adjust scoring prompts to match your niche (sales, engineering, healthcare).
• Add custom filters for target companies or industries.
• Change outreach tone to align with your brand voice.
• Limit by score (e.g., only push candidates with score ≥4).

Security & best practices

• Store all keys in n8n Credentials (never in nodes).
• Use Set nodes to centralize editable variables (title, location, filters).
• Always add sticky notes in your workflow explaining steps.
• Rename nodes clearly for readability.

Troubleshooting

• No candidates found? Loosen title variations or broaden location.
• Low fit scores? Refine keywords and required skills in scoring prompts.
• Airtable errors? Double-check Base ID, Table ID, and field names.
• API rate limits? Enable batching/pagination and increase intervals.

SEO title:
Build candidate shortlists from a job description to Airtable with Apollo, AI scoring, and personalized outreach

Keywords: recruiting automation, Apollo people search, candidate enrichment, AI scoring, Airtable recruiting CRM, LinkedIn outreach, n8n workflow template

🔗 Nodes Used

Airtable, HTTP Request, Basic LLM Chain, Anthropic Chat Model, OpenAI Chat Model, Auto-fixing Output Parser

📥 Import

Download workflow.json and import into n8n: Workflow menu → Import from File

📖 Importing guide · 🔑 Credential setup