# AI Job Search Agent — No API Key Needed (`nomad-agent/ai-job-search-agent`) Actor
AI agent that scans the open web for job postings beyond any single job board — no API key required, the AI is included. Returns an LLM match score with reasoning, salary, and HTTP-verified live links, with delta new-only monitoring for cheap scheduled runs.
- **URL**: https://apify.com/nomad-agent/ai-job-search-agent.md
- **Developed by:** [Nomad.Dev](https://apify.com/nomad-agent) (community)
- **Categories:** Jobs, AI, Agents
- **Stats:** 3 total users, 1 monthly users, 60.0% runs succeeded, 0 bookmarks
- **User rating**: No ratings yet
## Pricing
from $8.00 / 1,000 job results
This Actor is paid per event. You are not charged for the Apify platform usage, but only a fixed price for specific events.
Since this Actor supports Apify Store discounts, the price gets lower the higher subscription plan you have.
Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event
## What's an Apify Actor?
Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases.
In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours,
and optionally produces a well-defined JSON output, datasets with results, or files in key-value store.
In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server.
Actors are written with capital "A".
## How to integrate an Actor?
If asked about integration, you help developers integrate Actors into their projects.
You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready.
The best way to integrate Actors is as follows.
In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md):
```bash
npm install apify-client
```
In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md):
```bash
pip install apify-client
```
In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md):
````bash
# MacOS / Linux
curl -fsSL https://apify.com/install-cli.sh | bash
# Windows
irm https://apify.com/install-cli.ps1 | iex
```bash
In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md).
If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md).
For usage examples, see the [API](#api) section below.
For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt).
# README
## AI Job Search Agent — No API Key Needed
An AI agent that hunts the **open web** for job postings matching your query — company career pages, ATS boards, niche sites, anywhere a single job board wouldn't cover.
**No API key. No LLM account. No setup.** Type what you're looking for, hit Run. The AI is included in the price.
> Most "AI job" tools on the store either just re-serve one board's index, or make you go get an Anthropic/OpenAI key first. This one searches the live web itself, and the AI comes bundled.
### Why this and not a job-board scraper
| | Board scrapers (LinkedIn, Indeed, Hiring.Cafe…) | **This agent** |
|---|---|---|
| Coverage | One board's index | The **open web** — employer career pages + ATS boards that never hit a big board |
| Ranking | Keyword match | **LLM match score 0-100 with a written reason**, best-first |
| Dead links | Common | Every link **HTTP-verified live** before it's returned |
| Salary | Only if the board has a field | Copied **verbatim from the posting**, never guessed |
| Setup | — | **No API key needed** |
### What you get
One flat JSON record per job posting, sorted best-match-first.
| Field | Meaning |
|---|---|
| `matchScore` | **0-100 LLM rating** of how well this posting fits your request |
| `matchReasoning` | One sentence on *why* it scored that — the fit/mismatch signals it weighed |
| `title` | Job title, copied character-for-character from the posting |
| `company` | Hiring company / organisation |
| `location` | Location (may include remote hints) |
| `salary` | Compensation **exactly as stated** on the posting (`"$120k–$150k"`, `"Competitive"`). `null` when the posting states none — the agent never invents a figure |
| `url` | Direct link to the posting on the employer's own site or their ATS |
| `postedAt` | Posting date (`YYYY-MM-DD`) |
| `snippet` | 1-3 sentence summary of the role |
| `verified` | `true` only when the live-link check actually confirmed the URL |
| `isNew` | Present on delta runs — posting not seen in a previous run |
### Input
Everything is optional — describe the job in plain English and let the agent do the rest.
```json
{
"keywords": ["python", "backend"],
"locations": ["remote"],
"userDescription": "Senior Python backend engineer, fully remote, product company. Prefer fintech or dev tooling.",
"remote": "remote-only",
"seniority": "senior",
"titleExclude": ["intern"],
"maxItems": 15,
"onlyNewSinceLastRun": false
}
````
`userDescription` is the strongest signal — it's what each posting's `matchScore` is judged against.
### Cheap job alerts: `onlyNewSinceLastRun`
Turn it on and schedule the actor. Postings already seen in a previous run are dropped **before** they're pushed, so **you are not billed for them**. A daily run then costs only whatever is genuinely new that day — often a handful of results, sometimes zero.
### Pricing
**$0.005 per run start + $0.01 per job returned.** No subscription, no rental, no minimum charge.
- 15 jobs ≈ **$0.16**
- A daily delta run that finds 3 new jobs ≈ **$0.04**
- A run that finds nothing, or fails upstream, costs **$0.005 or less** — the per-result fee only fires on results actually delivered, and a failed run is never charged at all.
**The AI is included.** There is no second bill: no Anthropic key, no OpenAI key, no token charges landing on your account later.
> Want to run it on your own LLM key instead, and pay less per result? The BYOK twin — [AI Job Search Agent — Open-Web Job Finder](https://apify.com/nomad-agent/web-search-scraper) — is $3/1,000 results, but you supply and pay for an Anthropic or Mistral key on top.
### Verification — what "verified" does and doesn't mean
`verified: true` means one thing: at run time, the posting URL was **HTTP-reachable and did not redirect to the site's homepage**. It is not a claim that the role is still open or that the posting is accurate. Results are kept (with `verified: false`) when the check is inconclusive — a timeout or a 403 from a bot-defended site is not proof a job is gone, so ambiguous cases aren't punished. Only unambiguous 404/410s and homepage redirects are dropped.
### Integrations
Send results straight to Google Sheets, Slack, Make, Zapier or any webhook via [Apify integrations](https://apify.com/integrations) — no code required, or pull the dataset over the [API](https://docs.apify.com/api/v2).
### Use cases
- Long-tail job discovery beyond the big boards
- A scored, deduped daily job alert (schedule + `onlyNewSinceLastRun`)
- Passive-candidate tooling — find who's hiring for X
- Niche-role hunting (rare stacks, rare titles)
- Backfilling gaps in board coverage
### FAQ
**Do I really not need an API key?**
Correct. The AI runs on our key and is priced into the per-result fee. You need nothing but an Apify account.
**Is it legal to scrape job postings?**
This Actor reads only publicly available job postings — data any visitor can see without logging in. No data behind authentication is touched. Review the target site's terms and your local regulations for your specific use case.
**Do I need an account on the target site?**
No. Postings are discovered via web search and fetched from public pages — no login, cookies or session tokens.
**Why did I get fewer results than `maxItems`?**
The agent only returns postings that survive its checks: it vetoes careers-index pages, closed/expired roles, and third-party repost boards. You are only charged for what it actually returns, so a short run is a cheap run.
**Does the agent invent salaries or dates?**
No. Both are copied from the posting when stated and left `null` when not. The prompt explicitly forbids guessing.
***
⭐ **Finding this useful?** Leaving a review on the Actor page genuinely helps others find it — and tells us what to build next.
🐛 Found a bad result or a bug? Open an issue on the Actor's **Issues** tab and it'll get looked at.
***
**From the maker of [Oink](https://github.com/Exdenta/OinkAIJobSearch)** — an open-source, AI-powered job-search bot for Telegram that runs on these Actors. [Try the free bot](https://t.me/job_search_everyday_bot), get a managed instance at [oinkjobsearch.com](https://oinkjobsearch.com), or browse the [full catalog of 50+ Actors](https://apify.com/nomad-agent).
# Actor input Schema
## `keywords` (type: `array`):
Role or technology keywords the agent should search for (e.g. frontend, react, typescript). Each entry is one keyword or short phrase.
## `locations` (type: `array`):
Preferred locations, or remote. The agent biases results toward these and skips obvious mismatches.
## `userDescription` (type: `string`):
Free-text description of the role you want. This is the agent's primary signal — and the main thing each posting's matchScore / matchReasoning is judged against. A sentence or two works well.
## `remote` (type: `string`):
Remote work preference. Free text — the AI interprets it (e.g. any, remote-only, hybrid, on-site).
## `seniority` (type: `string`):
Target seniority level. Free text — the AI interprets it (e.g. junior, mid, senior, lead, principal — or any).
## `titleMustMatch` (type: `array`):
The agent prefers postings whose title contains at least one of these terms. A hint, not a hard filter — equivalent titles still qualify.
## `titleExclude` (type: `array`):
The agent skips postings whose title contains any of these terms.
## `maxItems` (type: `integer`):
Maximum number of job postings to return (1-50; values outside that range are clamped, not rejected). The agent may return fewer if it cannot find enough high-quality matches — you are only charged for what it actually returns.
## `maxAgeHours` (type: `integer`):
Preferred maximum age of postings in hours (default 168 = one week). The agent prefers fresh postings but may include older ones when fresh results are scarce.
## `onlyNewSinceLastRun` (type: `boolean`):
Delta / monitoring mode: only output postings not already seen in a previous run that also had this flag on. Already-seen postings are dropped before push and are not billed, so this is the cheapest way to run the agent on a schedule and pay only for genuinely new jobs. New records carry isNew: true.
## Actor input object example
```json
{
"keywords": [
"frontend",
"react",
"typescript"
],
"locations": [
"remote",
"Europe",
"Spain"
],
"userDescription": "Looking for a senior React engineer role at a product company, ideally in fintech or developer tooling, fully remote within Europe.",
"remote": "any",
"seniority": "any",
"titleMustMatch": [
"frontend",
"react"
],
"titleExclude": [
"intern",
"manager"
],
"maxItems": 15,
"maxAgeHours": 168,
"onlyNewSinceLastRun": false
}
```
# Actor output Schema
## `dataset` (type: `string`):
No description
# API
You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup.
## JavaScript example
```javascript
import { ApifyClient } from 'apify-client';
// Initialize the ApifyClient with your Apify API token
// Replace the '' with your token
const client = new ApifyClient({
token: '',
});
// Prepare Actor input
const input = {
"keywords": [
"python",
"backend"
],
"locations": [
"remote"
]
};
// Run the Actor and wait for it to finish
const run = await client.actor("nomad-agent/ai-job-search-agent").call(input);
// Fetch and print Actor results from the run's dataset (if any)
console.log('Results from dataset');
console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`);
const { items } = await client.dataset(run.defaultDatasetId).listItems();
items.forEach((item) => {
console.dir(item);
});
// 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs
```
## Python example
```python
from apify_client import ApifyClient
# Initialize the ApifyClient with your Apify API token
# Replace '' with your token.
client = ApifyClient("")
# Prepare the Actor input
run_input = {
"keywords": [
"python",
"backend",
],
"locations": ["remote"],
}
# Run the Actor and wait for it to finish
run = client.actor("nomad-agent/ai-job-search-agent").call(run_input=run_input)
# Fetch and print Actor results from the run's dataset (if there are any)
print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"])
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
print(item)
# 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start
```
## CLI example
```bash
echo '{
"keywords": [
"python",
"backend"
],
"locations": [
"remote"
]
}' |
apify call nomad-agent/ai-job-search-agent --silent --output-dataset
```
## MCP server setup
```json
{
"mcpServers": {
"apify": {
"command": "npx",
"args": [
"mcp-remote",
"https://mcp.apify.com/?tools=nomad-agent/ai-job-search-agent",
"--header",
"Authorization: Bearer "
]
}
}
}
```
## OpenAPI specification
```json
{
"openapi": "3.0.1",
"info": {
"title": "AI Job Search Agent — No API Key Needed",
"description": "AI agent that scans the open web for job postings beyond any single job board — no API key required, the AI is included. Returns an LLM match score with reasoning, salary, and HTTP-verified live links, with delta new-only monitoring for cheap scheduled runs.",
"version": "0.1",
"x-build-id": "KJ18VCvxWoxJoj22s"
},
"servers": [
{
"url": "https://api.apify.com/v2"
}
],
"paths": {
"/acts/nomad-agent~ai-job-search-agent/run-sync-get-dataset-items": {
"post": {
"operationId": "run-sync-get-dataset-items-nomad-agent-ai-job-search-agent",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
},
"/acts/nomad-agent~ai-job-search-agent/runs": {
"post": {
"operationId": "runs-sync-nomad-agent-ai-job-search-agent",
"x-openai-isConsequential": false,
"summary": "Executes an Actor and returns information about the initiated run in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK",
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/runsResponseSchema"
}
}
}
}
}
}
},
"/acts/nomad-agent~ai-job-search-agent/run-sync": {
"post": {
"operationId": "run-sync-nomad-agent-ai-job-search-agent",
"x-openai-isConsequential": false,
"summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.",
"tags": [
"Run Actor"
],
"requestBody": {
"required": true,
"content": {
"application/json": {
"schema": {
"$ref": "#/components/schemas/inputSchema"
}
}
}
},
"parameters": [
{
"name": "token",
"in": "query",
"required": true,
"schema": {
"type": "string"
},
"description": "Enter your Apify token here"
}
],
"responses": {
"200": {
"description": "OK"
}
}
}
}
},
"components": {
"schemas": {
"inputSchema": {
"type": "object",
"properties": {
"keywords": {
"title": "Keywords / role type",
"type": "array",
"description": "Role or technology keywords the agent should search for (e.g. frontend, react, typescript). Each entry is one keyword or short phrase.",
"items": {
"type": "string"
}
},
"locations": {
"title": "Preferred locations",
"type": "array",
"description": "Preferred locations, or remote. The agent biases results toward these and skips obvious mismatches.",
"items": {
"type": "string"
}
},
"userDescription": {
"title": "Describe what you're looking for (optional)",
"type": "string",
"description": "Free-text description of the role you want. This is the agent's primary signal — and the main thing each posting's matchScore / matchReasoning is judged against. A sentence or two works well."
},
"remote": {
"title": "Remote preference",
"type": "string",
"description": "Remote work preference. Free text — the AI interprets it (e.g. any, remote-only, hybrid, on-site).",
"default": "any"
},
"seniority": {
"title": "Seniority level",
"type": "string",
"description": "Target seniority level. Free text — the AI interprets it (e.g. junior, mid, senior, lead, principal — or any).",
"default": "any"
},
"titleMustMatch": {
"title": "Title should contain",
"type": "array",
"description": "The agent prefers postings whose title contains at least one of these terms. A hint, not a hard filter — equivalent titles still qualify.",
"items": {
"type": "string"
}
},
"titleExclude": {
"title": "Title must NOT contain",
"type": "array",
"description": "The agent skips postings whose title contains any of these terms.",
"items": {
"type": "string"
}
},
"maxItems": {
"title": "Max items",
"type": "integer",
"description": "Maximum number of job postings to return (1-50; values outside that range are clamped, not rejected). The agent may return fewer if it cannot find enough high-quality matches — you are only charged for what it actually returns.",
"default": 15
},
"maxAgeHours": {
"title": "Max posting age (hours)",
"type": "integer",
"description": "Preferred maximum age of postings in hours (default 168 = one week). The agent prefers fresh postings but may include older ones when fresh results are scarce.",
"default": 168
},
"onlyNewSinceLastRun": {
"title": "Only new since last run",
"type": "boolean",
"description": "Delta / monitoring mode: only output postings not already seen in a previous run that also had this flag on. Already-seen postings are dropped before push and are not billed, so this is the cheapest way to run the agent on a schedule and pay only for genuinely new jobs. New records carry isNew: true.",
"default": false
}
}
},
"runsResponseSchema": {
"type": "object",
"properties": {
"data": {
"type": "object",
"properties": {
"id": {
"type": "string"
},
"actId": {
"type": "string"
},
"userId": {
"type": "string"
},
"startedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"finishedAt": {
"type": "string",
"format": "date-time",
"example": "2025-01-08T00:00:00.000Z"
},
"status": {
"type": "string",
"example": "READY"
},
"meta": {
"type": "object",
"properties": {
"origin": {
"type": "string",
"example": "API"
},
"userAgent": {
"type": "string"
}
}
},
"stats": {
"type": "object",
"properties": {
"inputBodyLen": {
"type": "integer",
"example": 2000
},
"rebootCount": {
"type": "integer",
"example": 0
},
"restartCount": {
"type": "integer",
"example": 0
},
"resurrectCount": {
"type": "integer",
"example": 0
},
"computeUnits": {
"type": "integer",
"example": 0
}
}
},
"options": {
"type": "object",
"properties": {
"build": {
"type": "string",
"example": "latest"
},
"timeoutSecs": {
"type": "integer",
"example": 300
},
"memoryMbytes": {
"type": "integer",
"example": 1024
},
"diskMbytes": {
"type": "integer",
"example": 2048
}
}
},
"buildId": {
"type": "string"
},
"defaultKeyValueStoreId": {
"type": "string"
},
"defaultDatasetId": {
"type": "string"
},
"defaultRequestQueueId": {
"type": "string"
},
"buildNumber": {
"type": "string",
"example": "1.0.0"
},
"containerUrl": {
"type": "string"
},
"usage": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "integer",
"example": 1
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
},
"usageTotalUsd": {
"type": "number",
"example": 0.00005
},
"usageUsd": {
"type": "object",
"properties": {
"ACTOR_COMPUTE_UNITS": {
"type": "integer",
"example": 0
},
"DATASET_READS": {
"type": "integer",
"example": 0
},
"DATASET_WRITES": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_READS": {
"type": "integer",
"example": 0
},
"KEY_VALUE_STORE_WRITES": {
"type": "number",
"example": 0.00005
},
"KEY_VALUE_STORE_LISTS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_READS": {
"type": "integer",
"example": 0
},
"REQUEST_QUEUE_WRITES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_INTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"DATA_TRANSFER_EXTERNAL_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_RESIDENTIAL_TRANSFER_GBYTES": {
"type": "integer",
"example": 0
},
"PROXY_SERPS": {
"type": "integer",
"example": 0
}
}
}
}
}
}
}
}
}
}
```