ATS Tech Stack Scraper

💰 $5.05 / 1 000 rows  ·  pay only for results  ·  no credit card to try

We do the dirty work so your dataset stays clean. 😈

B2B tech-stack intel from public job posts — no $39-$399/mo SaaS bill. Point this Actor at any company's Greenhouse, Lever or Ashby board and get one structured row per active job, including a deduplicated list of canonical tech names (Postgres, Django, AWS, Kubernetes...) detected directly from the job description.

Sales reps qualifying accounts, recruiters sourcing by skill, and competitive-intelligence analysts mapping vendor footprint all need this signal. Commercial tools (TheirStack, Wappalyzer, BuiltWith) charge subscription fees for the same data. This Actor hits the public ATS APIs directly — no scraping, no browser, no auth — and emits a flat, Pydantic-validated dataset ready for any CRM enrichment pipeline.

🎯 What this scrapes

Three ATS platforms, one schema:

1. Greenhouse — boards-api.greenhouse.io/v1/boards/{token}/jobs?content=true (public, no auth)
2. Lever — api.lever.co/v0/postings/{token} (public, no auth)
3. Ashby — api.ashbyhq.com/posting-api/job-board/{token} (public, no auth; token is case-sensitive — Ramp, not ramp)

For each active job posting the Actor pulls the title, location, department, full HTML/plain-text description, and the public URL — then runs a case-insensitive word-boundary regex against a curated vocabulary of ~110 canonical tech names. The result is a single column you can pivot or filter without per-company string normalization.

Field	Type	Description
ats	string	greenhouse, lever, or ashby
company_token	string	Board slug passed to the ATS
job_id	string	ATS-canonical job id
title	string	Job posting title
location	string | null	Location string (Remote, NYC, Berlin...)
department	string | null	Department / team
url	string	Public job-post URL
description_text	string	Plain-text description (HTML stripped)
detected_techs	string[]	Sorted, deduplicated canonical tech names
posted_at	string | null	ISO 8601 UTC publication timestamp
scraped_at	string	ISO 8601 UTC row-creation timestamp

🔥 Features

• Three ATSs, one schema — Greenhouse, Lever, Ashby normalized to identical row shape.
• Curated tech vocabulary — ~110 canonical names spanning languages (Python, Go, Rust), frameworks (Django, React, FastAPI), databases (Postgres, MongoDB, Redis, Snowflake), cloud (AWS, GCP, Azure, Vercel), infra (Kubernetes, Terraform, Docker), CI/CD, observability, and ML/data tools.
• Per-company isolation — one bad token (404 from Lever, typo on Ashby) does not abort the run; the others still produce data.
• No browser, no auth — pure HTTP with curl-cffi browser-TLS impersonation; low compute footprint and fast runs.
• Pydantic v2 validation — every input and every output row is model-validated.
• Filter knobs — maxJobsPerCompany cap and minTechsDetected floor.
• Exponential backoff on 429 / 503 with Retry-After honoured.

💡 Use cases

• B2B sales qualification — enrich every Salesforce/HubSpot account with the company's live tech stack: "they hire Django + Postgres + AWS" tells you whether to pitch your Postgres-tuning SaaS.
• Recruiter sourcing — pull every "Senior Backend Engineer" role from your target accounts and filter by detected_techs to find teams that match your candidate's stack.
• Competitive intelligence — track which competitors are hiring for Kubernetes or Snowflake and infer their roadmap.
• CRM enrichment — replace TheirStack / BuiltWith / Wappalyzer subscriptions for the subset of buyers who publish their stack in JDs anyway.
• Investment research — map private-company tech footprint over time without paying for a Crunchbase Pro seat.
• Open-source stack maps — feed a public site that ranks the most-hired-for technologies in YC-backed startups.

⚙️ How to use it

1. Open the Actor input form.
2. Add one or more {companyToken, atsType} pairs under Companies to scrape (the form prefills with airtable on Greenhouse and Ramp on Ashby).
3. (Optional) Set Max jobs per company — leave empty for no cap.
4. (Optional) Set Minimum detected techs — 2 or 3 drops generic/non-engineering postings.
5. Leave Use Apify Proxy off unless you observe rate-limiting (public ATS APIs do not require it).
6. Click Start. Rows stream into the default dataset.

Quick examples

Two engineering-heavy companies, default settings:

{
  "companies": [
    { "companyToken": "airtable", "atsType": "greenhouse" },
    { "companyToken": "Ramp", "atsType": "ashby" }
  ]
}

Single Lever company, drop sales/marketing roles:

{
  "companies": [
    { "companyToken": "palantir", "atsType": "lever" }
  ],
  "minTechsDetected": 3
}

Three companies across all three ATSs, capped at 50 jobs each:

{
  "companies": [
    { "companyToken": "airtable", "atsType": "greenhouse" },
    { "companyToken": "palantir", "atsType": "lever" },
    { "companyToken": "Ramp", "atsType": "ashby" }
  ],
  "maxJobsPerCompany": 50,
  "minTechsDetected": 2
}

Pricing (Pay-Per-Event)

Event	Price	When
actor-start	$0.05	Once per run
result-row	$0.005	Per job row emitted

A typical 50-job run costs $0.05 + 50 × $0.005 = $0.30. Compare to TheirStack at $39-$399/month for the same signal.

How to find a company's ATS token

• Greenhouse: the path segment in boards.greenhouse.io/{token} or {token}.applytojob.com. Examples: airtable, figma, stripe.
• Lever: the path segment in jobs.lever.co/{token}. Examples: palantir, netflix, eventbrite.
• Ashby: the path segment in jobs.ashbyhq.com/{Token}. Case-sensitive — Ramp, PostHog, Linear work; the lowercase variants return zero jobs.

Output and limits

• Rows are pushed to the default Apify dataset as they are produced — long runs surface rows immediately.
• Apify FREE-tier default storage retains datasets for 7 days; use Actor.open_dataset(name="...") if you need to outlive that.
• The Actor exits successfully when at least one company yields one or more jobs. If every company returns zero (e.g. all tokens were misspelled), the run fails loud with a non-zero exit code.

Notes and caveats

• Tech detection is regex-based, not LLM-based — it is deterministic, free, and high-precision but will miss tools whose names are not in the curated vocabulary. Open a feedback request to add more.
• Greenhouse content is double-HTML-encoded (e.g. <div> for <div>); the parser unescapes twice before stripping tags.
• Lever's descriptionPlain often omits the "Requirements" bullet list; the parser concatenates every lists[].content chunk so skills hidden there are still detected.
• Ashby exposes both descriptionHtml and descriptionPlain — the parser prefers descriptionPlain when present.

Related Actors

• LLM Pricing Monitor — track live API pricing across OpenAI, Anthropic, Google, Mistral, Groq, Together AI, and DeepSeek in one normalized schema.
• GitHub Org Scraper — pair tech-stack signals from JDs with actual code-repo activity per org.
• Y Combinator Companies Scraper — combine YC funding signal with ATS-derived tech stack for a complete startup profile.

Support

• Author: DevilScrapes (profile)
• Issues / feature requests: open a feedback ticket on the Actor's Apify Store page.