Jobs Bing API
Returns one aggregated job listing: title, company, location, employment type, description, and apply URL.
GET /v1/jobs/bingLast updated November 2026Maintained by the SocialCrawl team
When to use the Jobs Bing API
Use it after bing/search, passing a job id from that list to read the description and apply link.
From the API reference
Returns one Bing-aggregated job: title, company, location, employment type, description, and apply URL. Use an id from GET /v1/jobs/bing/search.
Searching 69 platforms in parallel
What can you do with the Bing API?
The Bing endpoint gives you structured Jobs data with computed fields in a single request. No scraping infrastructure to build or maintain.
Example Request
# GET /v1/jobs/bing: 5 credits per call. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
# --max-time 60: the API's own time limit for this endpoint.
# --retry 3: retries timeouts, 429 and 5xx, honoring Retry-After.
# -o response.json keeps only the final attempt's body.
# One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
IDEMPOTENCY_KEY=$(od -An -N16 -tx1 /dev/urandom | tr -d ' \n')
curl -sS --max-time 60 --retry 3 -o response.json \
-H "x-api-key: YOUR_API_KEY" \
-H "Idempotency-Key: $IDEMPOTENCY_KEY" \
"https://www.socialcrawl.dev/v1/jobs/bing?id=NTU5NDY0MDEzLlJldHJv" && cat response.json# GET /v1/jobs/bing: 5 credits per call. Cache hits are free and failed calls are refunded.
# Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
import os
import random
import time
import uuid
import requests
API_KEY = os.environ.get("SOCIALCRAWL_API_KEY", "YOUR_API_KEY")
TIMEOUT_S = 60 # the API's own time limit for this endpoint.
MAX_RETRIES = 3
URL = "https://www.socialcrawl.dev/v1/jobs/bing"
def backoff(attempt):
# Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
return 2 ** attempt * (0.5 + random.random() / 2)
def socialcrawl(params):
# One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
idempotency_key = str(uuid.uuid4())
for attempt in range(MAX_RETRIES + 1):
try:
res = requests.get(
URL,
params=params,
headers={"x-api-key": API_KEY, "Idempotency-Key": idempotency_key},
timeout=TIMEOUT_S,
)
body = res.json()
except (requests.RequestException, ValueError):
# A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
if attempt == MAX_RETRIES:
raise
time.sleep(backoff(attempt))
continue
if body["success"]:
return body
error = body["error"]
# Branch on error["type"], never on the message text.
if error["type"] == "RESOURCE_NOT_FOUND":
return None # refunded: nothing to read
retry_after = res.headers.get("Retry-After")
# SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
permanent = error["type"] == "SERVICE_UNAVAILABLE" and retry_after is None
if not error.get("retryable") or permanent or attempt == MAX_RETRIES:
raise RuntimeError(f"{error['type']}: {error['message']} (request_id {body['request_id']})")
# Retry-After (seconds) wins; otherwise back off.
time.sleep(float(retry_after) if retry_after else backoff(attempt))
params = {
"id": "NTU5NDY0MDEzLlJldHJv",
}
body = socialcrawl(params)
if body is not None:
print(body["data"])// GET /v1/jobs/bing: 5 credits per call. Cache hits are free and failed calls are refunded.
// Check the price first for 0 credits: add dry_run=1 to the query. Nothing is fetched or charged.
const API_KEY = process.env.SOCIALCRAWL_API_KEY ?? "YOUR_API_KEY";
const TIMEOUT_MS = 60_000; // the API's own time limit for this endpoint.
const MAX_RETRIES = 3;
type Page = { next_cursor: string | null; has_more: boolean };
type SocialCrawlResponse =
| { success: true; data: any; pagination?: Page; credits_used: number; request_id: string }
| { success: false; error: { type: string; message: string; retryable: boolean }; request_id: string };
const sleep = (ms: number) => new Promise((resolve) => setTimeout(resolve, ms));
// Exponential backoff with jitter: about 1 s, 2 s, then 4 s.
const backoffMs = (attempt: number) => 2 ** attempt * 1000 * (0.5 + Math.random() / 2);
async function socialcrawl(url: URL) {
// One Idempotency-Key per request, reused on every retry, so a retried call is never charged twice.
const idempotencyKey = crypto.randomUUID();
for (let attempt = 0; ; attempt++) {
let res: Response;
let body: SocialCrawlResponse;
try {
res = await fetch(url, {
headers: {
"x-api-key": API_KEY,
"Idempotency-Key": idempotencyKey,
},
signal: AbortSignal.timeout(TIMEOUT_MS),
});
body = (await res.json()) as SocialCrawlResponse;
} catch (error) {
// A timeout, a dropped connection or a non-JSON gateway page: retry with the same key.
if (attempt >= MAX_RETRIES) throw error;
await sleep(backoffMs(attempt));
continue;
}
if (body.success) return body;
// Branch on error.type, never on the message text.
if (body.error.type === "RESOURCE_NOT_FOUND") return null; // refunded: nothing to read
const retryAfter = res.headers.get("Retry-After");
// SERVICE_UNAVAILABLE without Retry-After is a withdrawn endpoint: permanent.
const permanent = body.error.type === "SERVICE_UNAVAILABLE" && retryAfter === null;
if (!body.error.retryable || permanent || attempt >= MAX_RETRIES) {
throw new Error(`${body.error.type}: ${body.error.message} (request_id ${body.request_id})`);
}
// Retry-After (seconds) wins; otherwise back off.
await sleep(retryAfter ? Number(retryAfter) * 1000 : backoffMs(attempt));
}
}
const url = new URL("https://www.socialcrawl.dev/v1/jobs/bing");
url.searchParams.set("id", "NTU5NDY0MDEzLlJldHJv");
const body = await socialcrawl(url);
if (body) console.log(body.data);Parameters
| Parameter | Required | Description |
|---|---|---|
| id | Yes | Bing job id from bing/search. |
What does the Jobs Bing API return?
Every response follows one unified schema. Here is a real, unmodified response body, so you can see the exact fields you get back before spending a credit.
Example response
{
"success": true,
"platform": "jobs",
"endpoint": "/v1/jobs/bing",
"data": {
"job": {
"id": "MTE5OTc2NjYxOS5SZXRybw==",
"title": "Staff Software Engineer, Motion Planning",
"url": "https://de.linkedin.com/jobs/view/staff-software-engineer-motion-planning-at-aerovect-4459093710?trk=bingjobs",
"company": {
"id": null,
"name": "AeroVect",
"url": null,
"verified": null
},
"location": "Frankfurt, HE",
"listed_at": "22 days ago",
"easy_apply": null,
"remote": null,
"employment_type": "Full-time",
"experience_level": null,
"description": "Job descriptionWho We Are\n\n\n\nAeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.\n\n\n\nJob Description\n\n\n\nWe are looking for an experienced Staff Software Engineer who can design and build best-in-class planning systems for autonomous driving in structured, low-speed environments.\n\n\n\nIn this role, you'll be the technical backbone of the planning stack — owning the design and implementation of production-grade mission planning, behavior planning, and motion planning software. You'll work across the full planning pipeline to achieve category-defining vehicle autonomy for the airside, tackling hard problems in trajectory optimization, decision-making under uncertainty, and real-time constraint optimization.\n\n\n\nThis opportunity offers a deeply technical engineer the chance to shape a market-defining enterprise product that combines autonomous vehicle technology with a robotics-as-a-service (RaaS) business model. This role reports to our Planning Tech Lead and works closely with the autonomy engineering team.\n\n\n\nYou Will:\n\n\n\n\n\n- Design, implement, and iterate on the mission planner, behavior planner, and motion planner for autonomous ground support equipment operating in airport airside environments.\n\n- Drive key technical decisions across the planning stack — selecting algorithms, defining interfaces, and establishing the architecture that the team builds on.\n\n- Prototype and evaluate new planning approaches (e.g., optimization-based methods, search-based planners, learning-augmented pipelines) and bring the best ideas to production.\n\n- Collaborate cross-functionally with perception, controls, localization, and systems engineering teams to deliver an integrated autonomous driving system.\n\n- Establish and promote best practices in software development, functional safety, and systems engineering as they apply to the planning domain.\n\n- Mentor other engineers through technical guidance, code review, and design discussions.\n\n\n\n\n\nYou Have:\n\n\n\n\n\n- Bachelor's or Master's degree in Computer Science, Math, Electrical Engineering, Mechanical Engineering, Robotics, Physics, or a related field.\n\n- Extensive hands-on experience designing and implementing planning modules for autonomous systems shipped to production or deployed in real-world operations.\n\n- Strong programming skills in C++ (preferred) or Python, and experience with Linux-based operating systems.\n\n- Demonstrated ability to take ambiguous technical problems and drive them to well-architected solutions independently.\n\n- Excellent communication skills, proactiveness, and a strong sense of ownership.\n\n\n\n\n\nWe Prefer:\n\n\n\n\n\n- MS or Ph.D. in Computer Science, Robotics, or a related field. \n- Mastery of Modern C++ (14 and beyond) and safety-critical coding practices (e.g., MISRA, ISO 26262).\n\n- 5+ years of industry experience in planning for robotic ground vehicles. \n- In-depth understanding of DDS frameworks like ROS/ROS2 or other networking middleware.\n\n- Experience in startup environments, demonstrating adaptability to rapidly changing priorities.",
"apply_url": "https://de.linkedin.com/jobs/view/staff-software-engineer-motion-planning-at-aerovect-4459093710?trk=bingjobs",
"ext": {
"applicant_count": null,
"job_provider": null,
"salary_min": null,
"salary_max": null,
"salary_currency": null,
"country_code": null,
"linkedin_company_name": null,
"industries": null,
"job_function": null,
"accepting_applications": null,
"board": "bing"
}
}
},
"credits_used": 5,
"request_id": "req_example000000",
"cached": false,
"credits_remaining": 9999,
"redacted": true
}Live sample illustrating the unified response shape. Field values reflect the record you query.
How does the Jobs Bing API work?
Send a GET request with your API key and get back clean, structured JSON in our unified schema. Supported computed fields are populated when the source provides the required inputs.
Method
GET
Response
JSON
How do you scrape social media data in seconds?
The fastest social media scraping API for developers. Scrape profiles, posts, comments, and analytics from 69 platforms covering 10B+ monthly active users.
One schema, every platform
Query 69 platforms with identical response structures. Write your integration once.
Computed fields, not just scraped
When an endpoint supports these metrics and the source provides the required inputs, the normalized record includes engagement_rate, estimated_reach, content_category, and language. Ready to use.
See your data before you code
Visual Data Explorer. Paste any URL, get rich result cards, sortable tables, CSV export.
import requests
response = requests.get(
'https://www.socialcrawl.dev/v1/tiktok/profile',
params={'handle': 'charlidamelio'},
headers={'x-api-key': 'sc_YOUR_API_KEY'}
)
data = response.json(){
"success": true,
"platform": "tiktok",
"data": {
"author": {
"username": "charlidamelio",
"followers": 152400000
},
"engagement": {
"likes": 12400000000,
"engagement_rate": 0.087
},
"metadata": {
"language": "en",
"content_category": "lifestyle"
}
}
}Have a question? We got answers
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