New Job Alerts — Only New Postings from 27,000+ Career Sites

Watch 27,000+ company career sites and get back only the postings that appeared since your last run.

Every other job feed hands you the same thousands of rows every time and leaves you to diff them. This one remembers what it already showed you. Schedule it hourly or daily and each run returns a clean list of genuinely new openings — ready to pipe into Slack, an email digest, a spreadsheet or your own database.

Postings are read live from each employer's own applicant tracking system, so a row means the job is open on the company's careers page right now, with a direct apply link.

Platform	Boards watched
Greenhouse	5,578
Personio	5,172
SmartRecruiters	4,334
Workday	2,658
Lever	1,917
Workable	1,710
Ashby	1,596
Breezy HR	2,800
Rippling	1,298
Pinpoint	618
Total	27,681

No login, no cookies, no proxies, no API keys.

How the feed remembers

The first run seeds the feed and returns the most recent matching postings. Every run after that returns only what is new.

State is kept per feed name, in your own account. Run several alerts side by side — remote-react, berlin-sales, new-grad-ml — and give each its own feedId so they don't consume each other's new postings.

A posting older than lookbackDays (7 by default) is never counted as new, even on a first run. Raise it if you run the feed less often than weekly.

What you get

Field	Description
company / companySlug	Company name and its board slug
provider	Which ATS the posting came from
jobId	Stable per-posting ID
title	Job title
location	Location string as published
department	Department or team
employmentType	Full-time, contract, etc., where the ATS exposes it
remote	Remote flag, where the ATS exposes it
postedAt / updatedAt	Publication and last-modified timestamps
applyUrl	Direct application link on the employer's own site
salary	Pay range as the employer wrote it. Only Breezy and Ashby publish this; null elsewhere.
descriptionText	Full description, when includeDescription is on
scrapedAt	When this row was read, ISO 8601
firstSeenAt	When this feed first reported the posting

Results come back newest first.

Input

{
  "keywords": ["engineer", "developer"],
  "excludeKeywords": ["senior", "staff"],
  "remoteOnly": true,
  "feedId": "remote-eng",
  "lookbackDays": 7,
  "maxBoards": 300
}

Option	What it does
keywords	Keep titles containing any of these. Empty = every job.
excludeKeywords	Drop titles containing any of these.
locations	Keep postings whose location matches any entry.
remoteOnly	Keep only remote-flagged or remote-looking postings.
feedId	Names this feed's memory. One per alert you run.
lookbackDays	How far back a posting can be and still count as new.
companies / providers	Restrict to specific boards or ATS platforms.
maxBoards	How many boards to watch, largest employers first.
maxJobs	Cap on returned rows, so a run costs what you expect.
includeDescription	Off by default — alerts rarely need the full text.

Suggested setup

1. Run it once with your filters to seed the feed.
2. Add a Schedule — daily is a good default, hourly for competitive roles.
3. Connect the dataset to Slack, email, Zapier, Make or a webhook via Apify Integrations.

Each scheduled run then delivers only what is new.

A note on Workday

Workday is where most large enterprises post, and it is the biggest single source here — but its public listing endpoint carries less than the others. Workday rows have the company, title, location, requisition id and apply link, and no department, employment type or description; those live behind a per-posting request the price of a result cannot cover. Workday also reports posting age as text ("Posted Today", "Posted 30+ Days Ago"), so postedAt is exact when the age is exact and null when it is not — a missing date rather than an invented one. If you filter on posting date, Workday rows without a date are kept rather than dropped.

How the memory actually works

Worth understanding before you build a workflow on it, because the details decide what you get.

Where state lives. Each feed keeps a small record in a named key-value store inside your own Apify account. Nothing about your feed is stored on our side, and two customers watching the same employers never affect each other.

What gets remembered. Only postings that were actually delivered to you, plus earlier deliveries still inside the lookback window. A posting trimmed by maxJobs is not marked as seen — it goes out on the next run instead. That is deliberate: the backlog drains rather than disappearing.

Why the window matters. lookbackDays bounds both what counts as new and how big the memory gets. Without it the seen-set would grow towards the registry's million-plus postings and outgrow the 9 MB record limit. Postings age out of the memory on their own.

Postings with no date. Workday reports age as prose, so many of its rows have no timestamp. Those are judged purely by the seen-set: reported once, then suppressed. They cannot be filtered by lookbackDays because their age is genuinely unknown.

Several feeds at once. feedId names the memory. Run remote-react, berlin-sales and new-grad-ml side by side and each keeps its own position. Reusing one feedId across different filters is the one thing to avoid — the runs will consume each other's new postings.

Which fields each platform gives you

Field	Workday	SmartRecruiters	Greenhouse	Workable	Lever	Ashby	Breezy
title, company, location	yes	yes	yes	yes	yes	yes	yes
applyUrl	yes	yes	yes	yes	yes	yes	yes
postedAt	partial	yes	yes	yes	yes	yes	yes
department	no	yes	yes	yes	yes	yes	yes
employmentType	yes	yes	no	yes	yes	yes	yes
descriptionText	no	no	yes	yes	yes	yes	no
salary	no	no	no	no	no	yes	yes

Measured from real runs. includeDescription is off by default here because an alert is usually title, company and link — and because Workday and SmartRecruiters rows carry no description whatever the setting.

Recipes

A morning digest. Schedule daily, lookbackDays: 2, your keywords, and connect the dataset to email or Slack. Each run delivers only what opened since yesterday.

Hiring-intent alerts for sales. keywords: ["sales", "account executive"], lookbackDays: 3. A company opening sales headcount is a company with budget, and you hear about it the day it posts.

A watchlist of employers. Put slugs in companies and raise lookbackDays to 14. Useful for tracking competitors, acquisition targets, or companies you want to work for.

Feeding a job board without duplicates. Point it at your niche, run hourly, and append straight to your database. provider:companySlug:jobId is stable, so you can key on it safely.

Tuning

Symptom	What to change
Too many results per run	Lower maxJobs, or narrow keywords
One employer dominates	Lower maxJobsPerCompany (defaults to 25)
Missing roles you expected	Raise maxBoards, or widen lookbackDays
Nothing new most runs	Run less often, or widen the filters — an idle feed is working correctly
Want depth on a few firms	Set companies and raise maxJobsPerCompany

Cost

Pay per delivered posting. A run that finds nothing new costs nothing, which makes frequent scheduling cheap: the price tracks what actually changed rather than how often you look.

If you only need one ATS

This Actor is built for breadth — it does not ask you which applicant tracking system a company uses, because the registry already knows. When you only care about one platform, a narrower Actor is cheaper to reason about and its input schema has fewer knobs:

Actor	Coverage
Workday Jobs Scraper	2,658 Workday boards — paste a careers URL
SmartRecruiters Jobs Scraper	4,334 SmartRecruiters boards
Breezy HR Jobs Scraper	2,800 Breezy boards, with pay ranges
Workable Jobs Scraper	1,710 Workable boards, with full descriptions
Greenhouse Jobs Scraper	Any Greenhouse board by slug or URL, with full descriptions

All of them emit the same row shape as this Actor, so datasets from any combination can be unioned without a mapping layer.

Use it as an API

Most people who rely on this Actor never open the Apify console after the first run — they call it from their own code and read the rows straight back. One request in, job rows out, no polling and no dataset id to chase:

curl -X POST "https://api.apify.com/v2/acts/starbright_overlap~new-jobs-feed/run-sync-get-dataset-items?token=YOUR_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"feedId": "my-feed", "keywords": ["engineer"], "maxJobs": 200}'

import requests

rows = requests.post(
    "https://api.apify.com/v2/acts/starbright_overlap~new-jobs-feed/run-sync-get-dataset-items",
    params={"token": "YOUR_TOKEN"},
    json={"feedId": "my-feed", "keywords": ["engineer"], "maxJobs": 200},
    timeout=300,
).json()

for r in rows:
    print(r["company"], "—", r["title"], "—", r["applyUrl"])

const rows = await (await fetch(
  'https://api.apify.com/v2/acts/starbright_overlap~new-jobs-feed/run-sync-get-dataset-items?token=YOUR_TOKEN',
  { method: 'POST', headers: { 'Content-Type': 'application/json' },
    body: JSON.stringify({"feedId": "my-feed", "keywords": ["engineer"], "maxJobs": 200}) },
)).json();

Your token is at Settings → Integrations in the Apify console. Keep maxJobs set to what you actually need — it is the cap that decides what the call costs.

Running it on a schedule instead

If you want the rows to arrive without asking, add a Schedule from the Actor page (Actions → Schedule) and point a webhook at your endpoint. A daily schedule plus the postedWithinDays filter is the usual setup for a job board or an alerting pipeline.

Pricing

Pay per result — you are charged per new posting delivered. A run that finds nothing new costs nothing.

Notes

• Boards are scanned largest-first, so a capped run watches the most active employers.
• Dead or rate-limited boards are skipped without aborting the run; details land in a FAILED_BOARDS record.
• The board registry is re-validated every month, so dead companies drop out on their own.

Freshness, measured rather than promised

Some employers leave requisitions open for years — across the registry, 15% of Greenhouse postings and about half of the largest SmartRecruiters boards are over a year old. That matters more for an alert feed than for a search: a posting that has sat open since 2017 is not news.

lookbackDays (7 by default) is the guard. A posting older than that is never treated as new, even on a first run. Raise it if you run the feed less than weekly; lower it to 1 or 2 for a tight daily alert.

Postings with no publication date are judged by the seen-set instead, so they are reported once and then suppressed. That is most Workday rows.

A note on Workday

Workday is where most large enterprises post, and it is the biggest single source here — Accenture, Walmart, CVS Health, Lowe's. Its public listing endpoint carries less than the others: Workday rows have company, title, location, requisition id and apply link, and no department, employment type or description. Workday also reports posting age as text ("Posted Today", "Posted 30+ Days Ago"), so postedAt is exact when the age is exact and null when it is not.

Frequently asked

How does it know what is new? It keeps a small record in your own account listing the postings it has already delivered, keyed by feed name. Each run returns what is not in that record. Nothing is stored on our side.

What happens on the very first run? It seeds the feed and returns the most recent matching postings, so the first run is useful rather than empty. Every run after that returns only what appeared since.

Can I run several alerts at once? Yes — give each its own feedId (remote-react, berlin-sales, new-grad-ml). Feeds have separate memories and do not consume each other's new postings.

What if nothing new appeared? The run returns nothing and costs nothing, since billing is per delivered posting.

I capped maxJobs and there were more new postings than that. Are they lost? No. Only what was actually delivered is remembered, so the remainder goes out on the next run. The backlog drains rather than disappearing.

Which ATS platforms are covered? Workday, Greenhouse, SmartRecruiters, Workable, Lever, Ashby, Breezy, Rippling and Pinpoint HR — 27,681 company boards in total.

Can I send new jobs straight to Slack or a sheet? Yes. Add an Apify Schedule to run it, then use the platform's integrations (Slack, Zapier, Make, webhooks, Google Sheets) on the dataset each run produces.