Best LinkedIn Jobs APIs in 2026 for Hiring Data

Key takeaways:

• LinkedIn's own Jobs API is not something you can buy. It sits inside Talent Solutions, requires an approved partnership, and publishes no self-serve tier and no price.
• Everything in this guide is a third-party route to LinkedIn-derived job data. Real free tiers exist (Fantastic Jobs, TheirStack), useful paid access starts around $45, and the ladders run to $1,500 per month at Coresignal Premium and $30,000 at Scrapingdog's top tier.
• Per-record pricing beats per-request pricing at scale. Techmap charges from EUR0.002 per job record while subscription tiers bill for volume you may not use.
• Job postings are the most reliable public buying signal in B2B, which is why this data sells far beyond recruiting.

Most people searching for a linkedin jobs api are about to hit the same wall. LinkedIn publishes a Job Posting API, it is documented on Microsoft's developer site, and you cannot get access to it by signing up. It lives inside LinkedIn Talent Solutions and requires an approved partnership, with no public pricing and no self-serve path.

A developer on r/linkedin described the underlying frustration well in a thread about querying LinkedIn jobs, wanting to filter job descriptions by keyword, region, contract type and remote status because LinkedIn's own search "sucks big time, especially when trying to use Boolean search." The replies were mostly other developers with the same problem. That is the state of the category: real demand, and an official door that stays shut.

So this guide covers the routes that are actually open. Eleven of them, with pricing verified from each vendor's own page in July 2026, and honest notes on what each one can and cannot legally or technically reach.

Why LinkedIn's Own Jobs API Is Not an Option

Being precise about this before you spend money matters, because a lot of content in this space is vague about it.

LinkedIn's Job Posting API exists to let approved applicant tracking systems and staffing partners push jobs onto LinkedIn and manage them. It is built for posting, not for searching. Access runs through the Talent Solutions partner program, which involves an application, a business relationship and a contract.

There is no tier you can buy with a credit card. There is no published rate card. And critically, it is not designed to answer the question most buyers actually have, which is "show me every company hiring for this role in this region right now."

So every practical option is a third-party provider that has assembled job data from job boards, company career sites, aggregators or scraping. Those providers differ enormously in method, legality posture and price, and that is what the rest of this guide compares. It is also why most of the workarounds people reach for, covered in our guide to LinkedIn prospecting tools, operate outside the official API entirely.

Is Collecting LinkedIn Job Data Legal?

Legality turns on how the data is collected, and the picture is more settled than five years ago without being fully resolved.

The Ninth Circuit's decision in hiQ Labs v. LinkedIn held that scraping publicly accessible pages likely does not constitute access "without authorization" under the Computer Fraud and Abuse Act, reaffirming its earlier ruling after the Supreme Court remanded the case. That is the closest thing to a green light that public-data collection has.

But it is narrower than it sounds. It addresses one federal statute. It does not override LinkedIn's user agreement, which prohibits scraping and automated access, and it does not protect anyone using fake accounts. LinkedIn sued Proxycurl in January 2025 over exactly that, and Proxycurl shut down permanently on July 4, 2025.

The consequence is a spectrum. Providers aggregating from career sites and public job boards sit safest. Providers scraping LinkedIn directly carry more risk and pass it to you. Providers acting through a logged-in account carry the most, since that is the behavior LinkedIn's terms address most directly. None of this is legal advice: if you are building on this data at scale, have counsel read your provider's terms.

The Best LinkedIn Jobs APIs in 2026

Job data is worth more than recruiting budgets suggest. The U.S. Bureau of Labor Statistics reported 7.6 million job openings on the last business day of May 2026, and each of those postings is a public statement about where a company is spending. The tools below turn that into something queryable.

Ratings weight transparent pricing and structured output. Raw HTML retrieval scores lower than parsed records even when cheaper.

ColdIQ

Best for: Hiring signals inside a wider GTM workflow

Overview: ColdIQ is a unified GTM data API, and its job-intelligence category routes to six providers behind one key: Career Site Jobs, Limadata, LinkedIn Jobs API, PredictLeads, Sumble and TheirStack.

That matters because hiring data is rarely the endpoint. You want the companies hiring a role, then the technology they run, then the decision maker, then a verified email. Holding four contracts to do that is the normal state of affairs, and it is the thing this collapses.

Be clear about what it is not. ColdIQ does not hold a LinkedIn Talent Solutions partnership and does not run its own scrapers. It is a routing and aggregation layer over providers that source job data themselves, which means its legal posture is inherited from those providers rather than independent of them.

What it adds is that the same key reaching job data also reaches 700+ endpoints across enrichment, technographics, intent and contact data, with responses that name the source and the credits used.

Key features:

• Six job-intelligence providers reachable through one key and one credit balance
• Job signals chainable directly into enrichment and contact endpoints without a second contract
• Responses return the source provider, so you know which upstream answered a job query
• MCP server for Claude Code, Codex and Cursor for agent-driven hiring research
• Automatic routing by fit, cost and accuracy across overlapping job sources
• 100+ published Claude Code skills covering targeting and enrichment sequences

Pricing: The entry plan is $99 per month with 2,000 credits; Pro doubles that to $199 for 5,000 and Scale reaches $499 for 15,000, with Enterprise quoted on volume. Commit annually and the price drops 30%. Unspent credits survive three months, and the playground needs no card.

Pros: job signals connect to enrichment on the same balance, six sources without six contracts, source attribution per response, credits roll over, agent-ready

Cons: it runs no scrapers of its own and holds no LinkedIn partnership, so it cannot reach anything its upstream providers cannot, and it is built for people comfortable calling an API

How to start using it:

• Run a job search in the free playground for the exact role you sell into.
• Issue a key and expose it to your code as `COLDIQ_API_KEY`.
• Hit the job intelligence endpoint and note which of the six providers served the result.
• Feed the companies that come back into an enrichment call without changing credentials.
• Install the MCP server if you want an agent running hiring research on its own.

Why it's a good linkedin jobs api: Hiring data is a means to an account, and this is the only entry where getting from the posting to the buyer does not require another vendor.

Final verdict: Right when job data is one input into a broader pipeline. If you need raw job feeds at volume and nothing else, buy a dedicated jobs vendor.

Start free on ColdIQ

Fantastic Jobs

Overview: Fantastic Jobs publishes a LinkedIn Job Search API through RapidAPI that does what most people actually want: structured search across LinkedIn job listings with real filters, up to 1,000 jobs per call.

Key features:

• Up to 1,000 job records returned per single API call, which makes bulk pulls cheap in request terms
• A separate expired jobs endpoint for historical analysis of what companies used to hire for
• Structured JSON with location, description, contract type and company fields

Pricing: The free Basic plan gives 250 jobs and 25 requests per month with a 1,000 requests per hour rate limit. Pro is $45 per month for 10,000 jobs and 5,000 requests at 5 requests per second. Ultra is $95 for 20,000 jobs and 10,000 requests at 15 per second. Mega is $175 for 50,000 jobs and 25,000 requests at 25 per second. A bandwidth allowance of 10,240MB is included, then $0.001 per additional MB.

Pros: the cheapest genuine LinkedIn job search available, 1,000 records per call is unusually generous, free tier needs no negotiation

Cons: hard monthly caps rather than overage billing, the bandwidth fee is easy to overlook when pulling large descriptions, and you are buying through a marketplace rather than direct

Why it's a good linkedin jobs api: For most teams, $45 per month for 10,000 structured LinkedIn job records is simply the best price-to-value ratio in this list.

Final verdict: The default starting point, and the one to try before anything more expensive.

TheirStack

Overview: TheirStack holds 192 million historical job postings and adds roughly 278,000 per day, but its real differentiator is that it treats jobs and technology as one dataset. You can search for companies hiring a role and filter by the tools mentioned in the posting.

Key features:

• Job search joined natively to technology detection, so a query can combine role and stack
• A jobs dataset and a technographics dataset queryable on the same credits
• Credits valid for 12 months, which suits periodic list-building rather than constant polling

Pricing: What matters for job work is the credit unit: one credit per job record, three per company. That makes the $59 entry plan worth 1,500 job pulls, and the $400 tier worth 50,000. Credits stay valid a full year, and a free tier of 200 credits per month lets you check coverage before committing.

Pros: the jobs-plus-technology join is genuinely unique, jobs cost a third of what company lookups cost, credits stay valid 12 months

Cons: company-level queries consume triple the credits of job queries, coverage aggregates many boards rather than being LinkedIn-specific, and the free tier is small

Why it's a good linkedin jobs api: Filtering hiring signals by the technology named in the posting removes most of the noise that makes raw job feeds unusable for sales.

Final verdict: The best pick when you care why a company is hiring, not just that it is.

Coresignal

Overview: Coresignal aggregates 15+ web sources into a dataset covering 468 million job postings, 70 million companies and 895 million employee records, sold through APIs and bulk datasets.

Key features:

• Jobs, company and employee APIs on one credit system, so a posting connects to the team behind it
• Historical headcount data and employee webhooks on the Premium tier for tracking growth over time
• Bulk dataset delivery in JSON, CSV or JSONL for warehouse analysis

Pricing: A free tier gives 200 Collect and 400 Search credits, valid 7 days rather than monthly. Paid API access starts at $49 per month, jumps to $800 for Pro, and reaches $1,500 for Premium with its 50,000+ Collect and 150,000+ Search credits. Paying yearly takes off 20%, and bulk datasets sit above $1,000 per month with no free option.

Pros: the largest historical job corpus here, employee data joins naturally to postings, multiple delivery formats

Cons: the gap between Starter at $49 and Pro at $800 leaves no middle ground, multi-source company records consume double credits, and the free trial expires after 7 days

Why it's a good linkedin jobs api: Historical depth is what makes hiring data predictive rather than merely current, and 468 million postings is the deepest well in this list.

Final verdict: Excellent at volume and awkward in the middle, where the pricing ladder has a hole.

Techmap

Overview: Techmap sells job data by the record rather than the subscription, covering 140+ countries since 2020, delivered through an API, direct datafeeds or AWS Data Exchange.

Key features:

• Live database search with per-record billing, so you pay only for jobs you actually take
• Country-scoped datafeeds for teams that want an entire market rather than a query
• AWS Data Exchange delivery for full historical and current access inside an existing cloud account

Pricing: The Job Data API starts from EUR0.002 per job record. Datasets and datafeeds start at EUR333 per month per country, as either a subscription or a one-time purchase. AWS Data Exchange access runs EUR4,800 per year per country for all historic and current postings. Free evaluation runs through AWS Data Exchange feeds or a freemium RapidAPI plan.

Pros: per-record pricing is the fairest model here for irregular usage, unusually broad international coverage, multiple delivery channels

Cons: dataset pricing is scoped per country which adds up fast for multi-market teams, pricing is quoted in euros, and the brand is less known than the alternatives

Why it's a good linkedin jobs api: At EUR0.002 per record, pulling 100,000 jobs costs about EUR200, which no subscription tier here matches for one-off projects.

Final verdict: The most economical option for bursty or project-based job data pulls.

Bright Data

Overview: Bright Data sells LinkedIn Job Listings as a maintained dataset, alongside LinkedIn People Profiles and Company Information, backed by large-scale scraping infrastructure.

Key features:

• A dedicated LinkedIn Job Listings dataset kept current by managed infrastructure
• Refresh-rate pricing so you pay less for less frequent updates
• Related LinkedIn datasets available on the same account for joining jobs to companies

Pricing: The dataset marketplace base rate is $2.50 per 1,000 records, with volume tiers from 100,000 records up to full-database access. Refresh discounts are substantial: 25% for biannual, 50% for quarterly and 80% for monthly refresh commitments. A minimum monthly commitment is billed at the start of the month, and exact per-tier dollar amounts are not published.

Pros: genuinely large-scale infrastructure, steep discounts for lower refresh cadence, related LinkedIn datasets on one account

Cons: exact tier pricing is not public so budgeting requires a sales conversation, minimum commitments make small tests expensive, and compliance requirements are heavier than a simple API subscription

Why it's a good linkedin jobs api: For bulk historical pulls measured in millions of records, dataset delivery beats API pagination on both cost and time.

Final verdict: The volume option, priced and contracted accordingly. Check Bright Data

Apify

Overview: Apify is a marketplace of prebuilt scrapers called actors, including several LinkedIn job actors, run on managed infrastructure with scheduling, proxies and storage included.

Key features:

• Multiple LinkedIn job actors available without writing or maintaining any scraping code
• Scheduling, proxy rotation, storage and webhooks handled by the platform
• The same account runs actors for adjacent sources, so job scraping sits beside everything else

Pricing: The free plan includes $5 of usage. Starter is $29 per month plus pay-as-you-go, Scale is $199 per month and Business is $999 per month. Compute units cost $0.20 each on Free and Starter, $0.16 on Scale and $0.13 on Business.

Pros: no scraper maintenance, wide selection of actors including third-party job APIs, low entry price

Cons: compute-unit billing makes costs genuinely hard to forecast before you run a job, actor quality varies by author, and you inherit the compliance posture of whichever actor you pick

Why it's a good linkedin jobs api: When you need a specific slice of job data that no packaged API returns, an actor gets you there without a scraping project.

Final verdict: The flexible option, best when your requirement is unusual enough that packaged APIs do not fit. Check Apify

SerpApi

Overview: SerpApi returns structured results across many search engines, including Google Jobs, which aggregates listings from across the web, many of which also appear on LinkedIn.

Key features:

• A Google Jobs engine returning structured job results with location and company fields
• Coverage across many other engines on the same key for adjacent research
• Legal protection included on listed plans, which is unusual in this category

Pricing: The free tier gives 250 searches per month. Starter is $25 per month for 1,000 searches, Developer is $75 for 5,000, Production is $150 for 15,000, and Big Data is $275 for 30,000. Enterprise is custom.

Pros: clean structured output, legal shield on paid plans, one key covers many other research needs

Cons: Google Jobs is not LinkedIn and the overlap is partial, results are search-shaped rather than database-shaped, and per-search pricing is expensive for bulk collection

Why it's a good linkedin jobs api: It is the lowest-risk route to job data, because it queries a search engine rather than touching LinkedIn at all.

Final verdict: A sensible compliance-first choice, provided you accept it is an adjacent source rather than a LinkedIn one.

Scrapingdog

Overview: Scrapingdog offers a dedicated LinkedIn endpoint inside a general scraping API, retrieving pages cheaply with proxy handling included.

Key features:

• A LinkedIn-specific endpoint rather than a generic fetch, which handles some of the structure for you
• Proxy rotation and rendering managed by the platform
• A long pricing ladder that scales from hobby volume to very high throughput

Pricing: There is a free tier, then Lite at $40 per month, Business at $500, Corporate at $2,000, and higher tiers reaching $30,000 per month.

Pros: very low entry cost, dedicated LinkedIn handling, scales a long way on one contract

Cons: it returns pages rather than enriched structured records so you build the parser, the compliance posture is yours rather than the vendor's, and the jump from $40 to $500 is abrupt

Why it's a good linkedin jobs api: When you need full control over parsing and want the cheapest possible retrieval, raw page access is the honest primitive.

Final verdict: For engineering teams that want raw material, not for anyone who wants clean records out of the box.

Lix

Overview: Lix focuses on LinkedIn data export with a small API attached, aimed at moderate volumes rather than continuous feeds.

Key features:

• Search-level exports that pull results from a LinkedIn search into structured form
• A free tier that includes real export volume rather than a token trial
• Email enrichment available on the same credits at a published per-record rate

Pricing: The Starter tier is free with 50 credits per month, 1,000 search-level exports and 3 users. API credit packs cost $49 for 500 credits on the Standard plan or $49 for 2,500 on the Organization plan, with 10 free API credits to test. Additional emails cost $0.15 each.

Pros: genuinely useful free tier, transparent per-email pricing, low commitment

Cons: API credit packs are small and the two-tier structure is confusing, volume ceilings are low compared to everything else here, and it operates closer to LinkedIn's terms than aggregator-based providers

Why it's a good linkedin jobs api: For small teams pulling hundreds rather than hundreds of thousands of records, it avoids paying for infrastructure you will not use.

Final verdict: Fine at small scale, and quickly outgrown.

JobsPikr

Overview: JobsPikr sells managed job feeds for job boards and labor-market analytics teams, turning raw postings into structured market signals.

Key features:

• Credit-based plans sized for continuous feed consumption rather than ad hoc queries
• Job data normalized across sources for analytics rather than left in source format
• A 7-day free trial on entry plans for evaluating fit before committing

Pricing: The Kick-off plan includes 1,000 credits and the Starter plan includes 5,000 credits, both with a 7-day free trial. JobsPikr does not publish per-plan dollar prices on its public pricing page, so the actual cost requires a conversation.

Pros: built specifically for feed-shaped consumption, normalized output suited to analytics, trial available before commitment

Cons: no published pricing at all, which makes comparison impossible without contacting sales, credit definitions are not detailed publicly, and it is oriented to job boards more than sales teams

Why it's a good linkedin jobs api: For teams building a job board or labor-market product, a managed normalized feed removes an entire engineering workstream.

Final verdict: Likely a good product for its niche, but the missing prices make it hard to recommend over transparent alternatives.

How We Chose These LinkedIn Jobs APIs

Every entry had to offer genuine programmatic access to job data, publish verifiable pricing or say plainly that it does not, and be operating as of July 2026.

We excluded Proxycurl entirely, which is worth saying given how often it still appears in older roundups. It shut down permanently on July 4, 2025 following LinkedIn's federal lawsuit, and its team now runs NinjaPear, which states on its homepage that it does not scrape LinkedIn. Any guide still recommending Proxycurl is out of date.

We also dropped Adzuna during verification: its developer API is real, but it publishes no commercial pricing or licensing terms, so it cannot be compared honestly against priced alternatives. Where a pricing page did not render prices, we say so rather than importing a number from an aggregator. JobsPikr is the clearest case, with plans named, credits listed and dollar figures absent.

What Should a LinkedIn Jobs Search API Return?

A linkedin jobs search api is only useful if its filters match how you actually segment. Most disappointment in this category comes from discovering the filter you need does not exist after you have paid.

• Full-text search across the job description, since titles are unreliable across companies
• Company identity resolved to a domain, so results join to your CRM
• Posting date and, ideally, an expiry or last-seen date
• Location filtering that handles remote and hybrid as distinct states
• Seniority and contract type as structured fields rather than free text

Description-level search is the one that separates useful tools from decorative ones. Titles are unreliable across companies, while the body of a posting names the actual tools, team and scope. If a provider only filters on title, it cannot answer most real segmentation questions.

How Do You Choose the Right LinkedIn Jobs API?

Start from volume and shape, because those two variables eliminate most of the list immediately.

If you need under 10,000 records per month and want structured output, Fantastic Jobs at $45 is hard to beat and its free tier lets you confirm coverage first. If you need job signals joined to technology or company data, TheirStack and Coresignal are the two that do that natively. If you need millions of records for analysis, Bright Data's datasets or Techmap's per-record API cost far less than paginating an API.

If your requirement is unusual, an Apify actor will reach data that packaged products do not. If your priority is minimizing legal exposure, SerpApi's Google Jobs route touches LinkedIn not at all.

Then check the pricing model against your usage pattern rather than your peak. Steady daily polling suits subscriptions. Quarterly bulk pulls suit per-record pricing, where Techmap's EUR0.002 per record means a 250,000-record pull costs about EUR500 with no ongoing commitment.

The mistake worth avoiding is buying for the volume you hope to reach rather than the volume you have. Every tier here scales up easily, and none of them refund you for a year of unused capacity.

How Much Does a LinkedIn Jobs API Cost?

Pricing in this category splits into three models that are genuinely hard to compare without normalizing, so the table below shows what each actually costs to pull a comparable amount of data.

Per-record pricing wins clearly for one-off pulls, and subscriptions win for continuous access where you would otherwise pay repeatedly for the same records. The crossover point sits somewhere around monthly usage, which is why the right question is not "what does it cost" but "how often do I need this refreshed."

Two hidden costs deserve attention. Fantastic Jobs charges $0.001 per MB above its 10,240MB bandwidth allowance, which matters when job descriptions are long. Bright Data requires a minimum monthly commitment billed at the start of the month, so small tests are disproportionately expensive.

Turning Job Postings Into Pipeline

Job data becomes a sales asset only when you narrow it. A raw feed of every posting in your ICP is noise, and most teams abandon it within a month.

The narrowing that works is role plus recency plus repetition. A single posting is weak evidence. Three postings for the same function inside six weeks is a team being built, which means budget was approved and a decision maker exists. Requiring all three conditions discards most of a raw feed, which is the point: what survives is small enough that a rep will actually work it.

Hiring is one of several signals worth watching together, and our guide to using intent signals covers how to combine them without drowning a rep in alerts. The related play, tracking when a known contact moves to a new company, is covered separately in our piece on tracking job changes.

The second useful pattern is the tool mentioned in the description. A posting that names a competitor's product tells you the account is committed, and one naming a category without a vendor tells you the decision may be open. TheirStack and Coresignal both support that query directly.

From there, the workflow is mechanical: resolve the company to a domain, enrich for the function owner, and reference the hiring context in the first line of outreach. That last step is where most of the value sits, because a message referencing a specific role a company is building reads as research rather than a blast. The same principle applies to other public LinkedIn activity, which we cover in our guides to LinkedIn buying signals and prospecting on LinkedIn.

If you would rather not stitch four vendors together to do that, running the whole chain on one key is the reason a unified layer exists. ColdIQ's API directory and MCP server documentation show what that chain looks like end to end, and the broader lead generation API picture covers what happens after the enrichment step.