What It Does
- Fetches active and historical job listings for a company using its domain
- Returns title, description, posting URLs, and timestamps for each job
- Filters by timeframe — last month, quarter, 6 months, or year
- Fetches up to 10,000 job postings per company
- Preserves your original data while appending one row per job
- Auto-handles naming conflicts (e.g.,
title_1iftitleexists already)
🏁 Getting Started
1
Add the Node
Drop Fetch Jobs anywhere in your flow — it’s ideal after enrichment.
2
Enter the Domain
Map or enter a domain — e.g.,
nrev.ai, or use @domain dynamically from earlier steps.3
Set Timeframe and Limit
Choose how far back to look and how many jobs to fetch:
- Timeframes: last month, 3 months, 6 months, or year
- Limit: up to 10,000 jobs via dropdown
4
Toggle Active Jobs Only
Choose whether to return only live roles or include historical ones too.
5
Run the Node
Each job becomes a new row — ready for scoring, tagging, or personalization.
Inputs
🛠️ Required Fields
-
Company Domain (✅)
Domain to fetch job data for (e.g.,nrev.ai).
Tip: Use@domainto map dynamically from earlier steps. -
Last Detected After (✅)
Filter for recency. Options include:Last monthLast 3 monthsLast 6 monthsLast year
-
Limit (✅)
Max number of job listings per company:100,200,500,1000,2000,5000,10000
Tip: Helps control data size and credit usage.
-
Active Jobs Only (✅)
Toggle ON for only current jobs, or OFF to include historical listings.
All inputs are validated via dropdowns — no manual entry errors or over-limit issues.
Output
Returns a job-level dataset for each company — one row per job:| Field | Description |
|---|---|
title | Job title |
description | Job description text |
posting_url | Link to the original job post |
job_first_seen | First date this job was detected |
job_last_seen | Most recent detection date |
How It Works
- Reads the input domain (
nrev.ai, or@domain) - Queries for active and/or historical jobs
- Filters based on your timeframe + volume
- Returns one row per job post
- Appends clean, conflict-free data
🚀 Use Cases & Prompts
| Use Case | Setup Example |
|---|---|
| Hiring Signal Scoring | Fetch jobs from @domain, score accounts hiring for GTM roles |
| Growth Intent Detection | Filter for job activity in the last 3 months |
| Outbound Personalization | Use job descriptions to write tailored cold emails |
| Market Mapping | Compare hiring across industries or regions |
✨ Pro Tips
⚠️ Important Considerations
🛠 Troubleshooting & Gotchas
| Symptom | Likely Cause | How to Fix It |
|---|---|---|
| Blank job fields | No jobs found or invalid domain | Try expanding timeframe or check mapping |
title_1 or similar | Field conflict with existing column | Use Rename node downstream |
| Long run time | Large limit selected | Lower limit or break into smaller batches |
📝 FAQ
Can I fetch jobs dynamically per row?
Can I fetch jobs dynamically per row?
Yes — use
@domain to reference earlier rows. Each will fetch jobs for its own domain.How far back can I look?
How far back can I look?
Up to 1 year. Choose from 1, 3, 6, or 12 months using the dropdown.
Is this only for live job postings?
Is this only for live job postings?
By default, yes — but turn OFF Active Jobs Only to include historical roles.
What if no jobs are found?
What if no jobs are found?
You’ll get a blank row for that company — no credits charged.
💰 Pricing
| Action | Credit Cost |
|---|---|
| Per 100 jobs (1 page) | 2 credits per page |
Credits are calculated per 100 job rows returned.
Example: Limit 1000 → 10 pages → 20 credits
No jobs = no credits charged
Example: Limit 1000 → 10 pages → 20 credits
No jobs = no credits charged
Use hiring signals to time your outreach, target high-growth accounts, and connect when they’re building — not stalling. 📈🧠