ACTION_ID: company_open_jobs_from_predictleads
NAME: PredictLeads: Find Open Jobs
CATEGORY: Company Enrichment
CREDITS: 1

Find a company's open job postings by domain, with optional title,
description-keyword and recency filters. Returns per-posting detail
including salary, seniority, location and category.

1. INPUTS

company_domain (type: url, required)
  Company Domain. Domain of the Company for which you want to find
  open jobs

filter_by_job_titles (type: string, optional)
  Filter by Job Titles. Filter for specific words or phrases in job
  titles, separated by comma (e.g. "Engineer, Marketing, Accountant")

filter_by_job_descriptions (type: string, optional)
  Filter by Job Descriptions. Filter for specific words or phrases in
  job descriptions, separated by comma (e.g. "Salesforce, HubSpot").

days_since_posted (type: number, optional)
  Days SInce Posted. Filter for jobs posted within the last X days.

max_number_of_postings (type: number, optional)
  Max Number of Postings. Max number of postings

2. OUTPUTS

job_count (number) — Number of total open jobs

jobs (structured_array) — Open Jobs found

  Columns — reference as {{<action_instance_id>.jobs.<column>}}:
    id (string) — ID field
    type (string) — Type of the object
    title (string) — Job title
    description (string) — Job description in plain text
    url (string) — URL to the job listing
    first_seen_at (string) — Timestamp when first seen
    last_seen_at (string) — Timestamp when last seen
    last_processed_at (string) — Timestamp when last processed
    contract_types (raw_array) — Contract type value
    category (raw_array) — Category name
    onet_data (json) — O*NET Data
    posted_at (string) — Posted at timestamp
    recruiter_s_data (json) — Recruiter's Data
    salary (string) — Salary range as a string
    salary_data (json) — Salary Data
    seniority (string) — Seniority level
    status (string) — Job status
    language (string) — Language used
    location (string) — Location
    location_data (raw_array) — Location Data
    tags (raw_array) — Tag label
    company_relation_ships_data (json) — Relationships Company Data

3. HOW TO CONFIGURE

Configure Action body:

{
  "inputs": {
    "company_domain": "{{input.company_domain}}",
    "filter_by_job_titles": "Engineer, Data Scientist",
    "filter_by_job_descriptions": "Salesforce, Snowflake",
    "days_since_posted": "30",
    "max_number_of_postings": "50"
  }
}

Field-by-field:
  - company_domain              Required. Bare domain.
  - filter_by_job_titles        Comma-separated phrases, OR-matched as a
                                contains filter on the title.
  - filter_by_job_descriptions  Same, matched against the description —
                                this is how you infer a tech stack from
                                hiring.
  - days_since_posted /         Number fields; pass them as quoted
    max_number_of_postings      strings.

4. KEY NOTES

- `days_since_posted` and `max_number_of_postings` are number fields —
  pass them quoted. Raw JSON numbers are ignored with an `unknown_field`
  warning.
- Filtering on `filter_by_job_descriptions` is a cheap technographic
  signal: a JD requiring "Salesforce admin experience" is hard evidence
  the company runs Salesforce.
- `job_count` is the count AFTER your filters are applied — use it
  directly as the gate for downstream steps.
- `jobs` is a `structured_array` with several `json` columns
  (`salary_data`, `onet_data`, `recruiter_s_data`); those need bracket
  access inside a `formula`, not dotted references.
- The credit cost is per call regardless of how many postings come back.

5. WHERE IT FITS IN A WORKFLOW

Pattern: company_open_jobs_from_predictleads (descriptions filter) ->
filter (job_count greater than 0) ->
get_employees_by_company_using_floqer_native -> outreach chain.

6. WHEN TO USE

Use company_open_jobs_from_predictleads to find companies actively
hiring for a role you sell into, or to infer a tech stack from what they
are hiring for.

7. WHEN NOT TO USE

Need technology detection from the website itself
  -> action-detail/company_tech_stack_enrichment_using_their_stack.txt

The signal you want is press coverage
  -> action-detail/company_news_events_from_predictleads.txt

Last updated: 2026-08-03.