Job Posting Monitor Clay-Ready Hiring Signal Discovery

📋 What can Job Posting Monitor do?

Give it role keywords and it returns the companies hiring for that role right now, one clean row per posting, with each company enriched with its domain, LinkedIn URL, employee count and industry.

This is the reverse of a domain-level ATS checker. You do not give it a company and ask "are they hiring?" You give it a role and ask "who is hiring for this?"

📦 What you get	⚙️ Features and integrations
🏢 Hiring companies, deduplicated to one row per posting 🔗 Domain and LinkedIn URL resolved per company 🧹 Staffing agencies and freelance marketplaces filtered out 🧾 16 flat fields, snake_case, Clay-native	🔍 Google Jobs discovery via your own SerpAPI key 🏷️ Company type classification on every row 🔄 Cross-run delta detection, only new postings ⬇️ Export to JSON, CSV, Excel, HTML or XML

Bought by anyone running role-triggered outbound: recruiters, staffing-adjacent vendors, and sellers whose buying signal is a specific role opening.

🚫 The keyword list is fully generic, and the editorial default is just a preset. It ships with proofreader, copy editor and content editor because that was the first use case, but the same actor tracks engineering, sales, marketing, operations or finance by changing the keywords.

💡 Why use Job Posting Monitor?

If you want	Read these fields
The hiring company	company_name, company_domain
An outreach target	company_linkedin_url
To size the account	employee_count, industry
To drop the wrong kind of company	company_type
The role and where to apply	job_title, job_url, location, is_remote
Recency and novelty	posting_date, is_new_posting
Why this row matched	matched_keyword, job_description_snippet

🧹 Filtering out the noise is most of the value

Raw job search results are dominated by staffing agencies and freelance marketplaces reposting the same roles. This actor filters both.

Staffing and recruitment agencies are filtered on both the company name and the job description text, because plenty of agencies do not have "recruitment" in their name. Freelance marketplaces (Upwork, Fiverr, Freelancer, Toptal and similar) are excluded by name, and the list is yours to extend.

Everything that survives is classified: direct_employer, staffing_agency, government or unknown. If you disagree with the filter, turn it off and filter on company_type yourself.

🔄 Re-runs only return what is new

is_new_posting and the built-in delta cache mean a scheduled run does not re-emit everything it already showed you. Pass previous_run_date if you would rather control the window yourself.

📋 What data can Job Posting Monitor extract?

16 fields per posting.

Field	What it holds
company_name	The hiring company
company_domain	Resolved canonical domain, or null
company_linkedin_url	Company LinkedIn page, the primary outreach field
employee_count, industry	Firmographics, where the company exposes them
company_type	direct_employer, staffing_agency, government or unknown
job_title	The role title
job_url	Direct apply or posting URL
posting_date	Normalized to ISO, best effort
source_board	google_jobs, greenhouse, lever or ashby
location, is_remote	Where the role is
job_description_snippet	First 500 characters of the description
matched_keyword	Which of your keywords this posting matched
is_new_posting	true when not seen in a prior run
run_date	When the run happened

⚠️ employee_count and industry are frequently null, because the firmographic source only reports them when a company exposes them. The company_size_min and company_size_max filters therefore apply only when a size is known, and will silently keep companies of unknown size. company_linkedin_url, the field most people actually act on, resolves for the large majority.

🛠️ How to find companies hiring for a role

1. Open the Input tab and put your role titles in keywords.
2. Paste a SerpAPI key into serpapi_key, or set a SERPAPI_KEY environment variable on the actor.
3. Set country and lookback_days to scope the search.
4. Leave the staffing and freelance filters on.
5. Click Start, then work the rows where company_type is direct_employer.

🧪 Using it in Clay

Point a Clay table at this actor's dataset, one Clay row per output row. The key columns are company_name, company_domain, company_linkedin_url, job_title and posting_date.

Use company_linkedin_url as the input to a LinkedIn step, and posting_date plus is_new_posting to prioritize fresh signals.

Schedule the actor and rely on the built-in delta cache, or pass previous_run_date, so each refresh only ingests new postings.

🌐 Choosing your job board sources

sources selects which boards a run searches. The default is google_jobs, which is what every earlier version did, so an existing saved input behaves exactly as it did before.

Sources run as an ordered chain, cheapest first, not all at once:

Tier	Source	Key needed	Billed per	What it covers
0	jobicy	none	nothing	Remote roles, marketing, writing, design and support heavy.
0	remotive	none	nothing	Remote roles, keyword searchable at the source.
0	arbeitnow	none	nothing	Europe heavy, strong on Germany and the Netherlands.
0	themuse	none	nothing	Mid market and enterprise employers in the United States.
0	remoteok	none	nothing	The newest 100 remote postings on Remote OK.
0	weworkremotely	none	nothing	The We Work Remotely feed, remote only.
0	himalayas	none	nothing	The newest pages of Himalayas, remote only.
1	adzuna	Adzuna app id and key	call	Indeed style aggregate coverage per country, dated at the source.
2	jobspipe	JobsPipe key	job returned	30 plus boards normalized, with the employer domain on the row.
2	google_jobs	SerpAPI key	search	The widest corpus: Indeed, LinkedIn, Glassdoor, ZipRecruiter and career pages.
2	theirstack	TheirStack key	job returned	Career sites and boards, with employer domain, LinkedIn URL and headcount on the row.

Tier 0 runs every keyword. Tier 1 runs only on keywords Tier 0 left short, and Tier 2 only on keywords still short after that, JobsPipe first and TheirStack last because its allowance is the smallest. A keyword is satisfied once the run has found enough_new_companies_per_keyword distinct new companies for it (default 3); when every keyword is satisfied the chain ends whatever budget is left. Between tiers every posting is checked against the cross-run delta cache, so a metered source is never asked for a posting the run already has.

Metered queries are narrowed to metered_window_days (default 2, today and yesterday). JobsPipe and TheirStack bill per job returned whether or not you have seen it before, and the delta cache dedupes after the bill, so the date window is what keeps those credits.

A posting that shows up on two boards is deduplicated on company plus normalized job title. The run log reports the raw count, the new count and the calls and credits spent per source and per country, and the same table is written to the run's key value store as RUN_SUMMARY.

countries loops several countries inside one run. Metered sources query each country separately; the Tier 0 boards are global remote boards and run once. Use the names Google Jobs accepts: United States, United Kingdom, Canada.

The seven Tier 0 boards need no credentials of any kind, so a run with sources: ["jobicy"] works on a fresh account with nothing configured.

🔑 The keys

Every metered source takes its key from the input first (serpapi_key, adzuna_app_id, adzuna_app_key, jobspipe_key, theirstack_key) and falls back to the matching environment variable on the actor. With neither, that source is skipped and the run says so. The Tier 0 boards still run.

Keys set in the actor's environment belong to the operator and are honored only for runs owned by the accounts the operator lists; any other account brings its own keys through the input.

⌨️ Input

Everything is on the Input tab. The options worth explaining:

Field	Type	Default	What it does
keywords	array	editorial preset	Role titles to search for. Any role works.
sources	array	["google_jobs"]	Which job boards to search, run as the chain above.
serpapi_key	string	none	Your SerpAPI key for google_jobs, unless SERPAPI_KEY is set on the actor.
adzuna_app_id, adzuna_app_key	string	none	Your Adzuna credentials for adzuna.
jobspipe_key, theirstack_key	string	none	Your JobsPipe and TheirStack keys.
country	string	United States	Geographic filter for one country.
countries	array	none	Several countries in one run; overrides country.
metered_window_days	integer	2	Date window for metered queries, 1 to 7.
enough_new_companies_per_keyword	integer	3	New companies that satisfy a keyword and stop its chain.
metered_run_cap	integer	50	Ceiling per metered source per country per run.
lookback_days	integer	30	Only return postings newer than this.
company_size_min, company_size_max	integer	none	Drop companies outside the range, when size is known.
exclude_staffing_agencies	boolean	true	Filter staffing and recruitment postings.
exclude_freelance_marketplaces	boolean	true	Filter Upwork, Fiverr and similar.
freelance_marketplaces	array	7 defaults	Override or extend the marketplace list.
remote_only	boolean	false	Only return remote postings.
previous_run_date	string	none	ISO date; only emit postings newer than this.
max_results	integer	100	Raw postings scanned before filtering.
max_companies	integer	40	Cap on unique companies enriched per run. Bounds sub-actor cost.

📤 Output

One flat row per posting, exportable as JSON, CSV, Excel, HTML or XML.

{
  "company_name": "Stripe",
  "company_domain": "stripe.com",
  "company_linkedin_url": "https://www.linkedin.com/company/stripe",
  "employee_count": 8000,
  "industry": "Financial Services",
  "company_type": "direct_employer",
  "job_title": "Senior Software Engineer",
  "job_url": "https://boards.greenhouse.io/example/jobs/123",
  "posting_date": "2026-06-25",
  "source_board": "google_jobs",
  "location": "San Francisco, CA",
  "is_remote": true,
  "job_description_snippet": "We are seeking a backend engineer to...",
  "matched_keyword": "software engineer",
  "is_new_posting": true,
  "posted_via": "LinkedIn",
  "search_country": "US",
  "degraded": false,
  "degradation_reason": null,
  "run_date": "2026-07-01T14:06:22.297Z"
}

search_country is the country a metered query ran for, null for a global remote board. degraded is true, with a plain reason, on a row whose enrichment did not finish inside its time budget: a null company_domain on such a row means unresolved, not absent. Identity, firmographics and LinkedIn each have their own budget, and LinkedIn runs last, so a slow LinkedIn lookup can cost a LinkedIn URL and nothing else.

source_board is the source you selected. posted_via is the board the posting was actually published through, as reported by that source, so you can see the board distribution behind a google_jobs run without reconstructing it from the URLs.

💡 Tips

• Work company_type: "direct_employer" first. It is the reason the filtering exists.
• Tighten lookback_days before raising max_results. Fresh postings convert better than deep ones.
• max_companies is your cost control. It bounds how much enrichment a run can trigger.
• Schedule it and filter on is_new_posting to turn this into a standing feed rather than a one-time list.
• Extend freelance_marketplaces with whatever else clutters your vertical.
• No SerpAPI key yet? Start with sources: ["jobicy", "remotive"]. No credentials needed.
• Group posted_via in your export to see which boards actually carry your role.

⚠️ Known limits

Discovery depth is bounded by max_results. Very high-volume keywords may need multiple runs or a tighter lookback_days.

Company enrichment is capped per run by max_companies, deliberately, to bound sub-actor cost.

Enrichment depends on name-to-domain resolution. Ambiguous or very small companies may not resolve, and those rows come back with a null domain and null firmographics rather than being dropped.

employee_count and industry coverage varies and is frequently null. The size filters apply only when a size is known.

Google Jobs coverage excludes some regions where the widget is disabled, including the EU.

Posting dates from aggregated boards are often relative, for example "25 days ago", and are normalized to a best-effort ISO date.

A SerpAPI key is required. Without one, discovery returns nothing.

❓ FAQ

Do I need a SerpAPI key?

Yes. Discovery runs on the SerpAPI google_jobs engine. The free tier covers 250 searches per month.

Why did a run return nothing?

Usually no key, or a keyword and country combination the selected source does not serve. The run sets a status message saying which, emits zero rows and exits cleanly rather than erroring.

A run that finds nothing costs nothing. Earlier versions pushed a single explanatory row when there were no new postings, and because a result is a dataset row, that row was billed as a result. It is not any more: those notices are status messages and log lines. If you have automation that reads a "no new postings" row, read the run status message instead.

Are staffing agencies really filtered out?

They are filtered on both company name and job description text, and anything that survives is labeled in company_type. If you would rather judge for yourself, turn the filter off and filter on that field.

Will a scheduled run keep showing me the same postings?

No. Cross-run delta detection means re-runs only emit postings you have not seen. is_new_posting carries the flag.

What happens if the enrichment sub-actors fail?

The row is still emitted with null enrichment fields and a structured error is logged. Discovery is never lost to an enrichment failure.

🧩 Want other GTM data?

Mamba Labs builds custom actors for B2B go-to-market teams. The public versions of that work live here on the Store, so our users get the same tooling we build under contract.

🕵️ Agent Accessibility Auditor	🤖 AI Tooling Detector
📡 B2B Buying Signals Aggregator	🚀 Prospect Engine
📝 Publishing Frequency Tracker	🦋 Bluesky Brand Presence Mapper
⏩ Sequencer Lead Push	🔄 Company Change-Event Feed
📇 Company Contact Details Extractor	🧭 Company Discovery List Builder
🏢 Company Firmographic Enricher	🪪 Company Identity Resolver
🌐 Company Social Presence Mapper	🏷️ Contact Classifier
📬 Domain Deliverability Checker	🔗 Domain to LinkedIn URL Resolver
🛒 Ecommerce Platform Profiler	✉️ Work Email Waterfall Finder
🎪 Event Presence Index	💵 Funding Record and Filings
💰 Funding and Press Signal Scanner	🐙 GitHub Organization Signal Scanner
🧑‍💼 GTM Hiring Signal Scraper	🧱 Tech Stack Detector
🎯 ICP Fit Scorer	🔑 Job Board Keyword Scanner
⚖️ Legal Entity Resolver	💼 LinkedIn Company Page Mapper
💬 LinkedIn Post Tracker and Comment Capture	📢 Meta Ad Library Monitor
📸 Instagram and Facebook Brand Mapper	📮 Outbound Stack Detector
📄 Page Finder and Extractor	👤 People Finder and Email Verifier
📌 Pinterest Brand Presence Mapper	🏛️ Government Contract Award Monitor
📅 Public Company Reporting Window Finder	👽 Reddit Brand and Mention Monitor
⭐ Trustpilot Reputation Enricher	👥 Team Page People Extractor
🎵 TikTok Brand Presence Mapper	📈 Website Traffic Rank Estimator
🏅 Workplace Program Detector	✖️ X Twitter Brand Presence Mapper
▶️ YouTube Channel Stats Extractor

Every actor in the suite takes a domain or a company and returns one flat row, so they stack in the same Clay table without reshaping anything.

🛠️ Need something custom built for you or your team? Tell us what you are trying to find and we will build it. Talk to Mamba Labs.

🆘 Support

Something wrong, or a company misclassified? Open an issue on the Issues tab with the keyword and the row, and we will look at it.

ℹ️ Sourcing and legal. Job postings come from the SerpAPI google_jobs engine against your own key, and from public job board APIs. Company enrichment comes from Mamba Labs fleet actors reading public company data. The actor stores no personal data: it returns companies, roles and postings, not people. You are responsible for how you use the output.

Built by Mamba Labs.