AHK.AI's web scraping job postings analysts spin up pipelines with rotating proxies, schedule management, and deduplication so HR tech products can observe demand in near real time. We enrich listings with standardized titles, SOC codes, salaries, employer metadata, and remote/hybrid tags before syncing to your database or API consumers.
What You'll Get
Job Title, Description, and URL
Company Name and Industry
Salary Ranges (Base, Bonus, Equity)
Required Skills and Tech Stack
Remote / Hybrid / On-site Status
Date Posted and Application Count
How We Deliver This Service
Our consultant manages every step to ensure success:
1
Target Definition: Define the roles, locations, or specific companies you want to track.
2
Scraper Config: I set up bots to handle different ATS structures (Greenhouse, Lever, Workday).
3
Extraction: Collecting data while respecting rate limits and anti-bot measures.
4
Parsing: Extracting structured data like 'Python' or '$150k' from unstructured descriptions.
5
Delivery: You receive a clean dataset ready for your analytics dashboard.
Yes, I can build custom scrapers for specific ATS systems like Greenhouse, Lever, and Workday to get data directly from the source.
How do you handle salary data?
I extract explicit salary ranges where available, and can also use NLP to parse salary mentions from the job description text.
Can you detect if a job is remote?
Yes, I classify jobs as Remote, Hybrid, or On-site based on the location field and keywords in the description.
Client Reviews
★★★★ 4.92
based on 131 reviews
★★★★★ 5
Demand signals, finally
We needed near real-time visibility into hiring trends across marketplace sellers and brands, but our previous scrape was noisy and full of duplicates. AHK.AI set up rotating proxies, scheduling, and deduplication that actually held up during peak hours. The enrichment was the difference maker: standardized titles, SOC codes, and remote/hybrid tags let our BI team build reliable dashboards. Salary ranges (base/bonus/equity) were surprisingly complete for the roles we track.
Project: Scraped job postings from 18 retail and marketplace job boards; enriched and synced to Snowflake for weekly demand reporting.
★★★★★ 5
Clean data into our API
We sell a recruiting analytics product and needed consistent job posting data with minimal engineering babysitting. Their pipeline handled rate limits with rotating proxies and kept a stable cadence on a cron schedule. The normalized job titles and SOC mappings reduced our model’s label drift, and the skill/tech stack extraction was accurate enough to power our search facets. They also pushed everything into our internal API format without us rewriting ETL.
Project: Built a scraping + enrichment pipeline for 12 sources and delivered JSON payloads to our ingestion API with dedupe keys.
★★★★ 4.5
Strong enrichment, minor gaps
We track clinical and non-clinical hiring (RN, MLT, revenue cycle) across hospital systems and staffing firms. The SOC coding and standardized titles made our workforce planning reports much cleaner. Remote/hybrid classification was generally right, though a few postings labeled “hybrid” in fine print came through as on-site. Support was responsive and adjusted rules quickly. Overall the data quality is a big step up from what we were manually compiling.
Project: Monitored postings from 25 hospital career sites and two aggregators; synced enriched fields to our Postgres warehouse.
★★★★★ 5
Great for competitive intel
Our team watches hiring at property management companies and proptech competitors to forecast expansion. AHK.AI delivered a steady feed with URLs, full descriptions, and clean company metadata (including industry) so we could segment by multifamily vs. commercial. The deduplication logic caught reposts across boards, which used to inflate our counts. Salary bands helped us benchmark leasing and maintenance roles across regions.
Project: Scraped 9 job boards plus 30 company career pages; enriched and delivered daily delta files to S3.
★★★★ 4
Solid pipeline, slower ramp
The end result is good: normalized titles, SOC codes, and reliable dedupe across reposted roles. We use the data to monitor hiring for quant, risk, and compliance positions at mid-market firms. The only drawback was onboarding took longer than we expected because a few sources had aggressive bot protection and required extra proxy tuning. Once stabilized, the scheduled runs have been consistent and the salary parsing is better than our in-house regex.
Project: Set up scraping for 15 finance employers and two niche boards; integrated enriched output into our data lake for trend analysis.
★★★★★ 5
Made our reports credible
We build monthly talent landscape reports for clients, and inconsistent job data was always the weak spot. AHK.AI’s enrichment (titles, company info, skills/stack, remote tags) gave us a dataset we can actually cite. I liked that they included base/bonus/equity ranges when available, which helps our compensation slides. The pipeline runs on a schedule and drops into our Airtable + warehouse without us chasing broken scrapers every week.
Project: Automated scraping from 6 major boards and 40 brand career pages; delivered enriched tables for client-ready dashboards.
★★★★ 4.5
Useful for plant hiring
We needed a better view of hiring demand for maintenance techs, process engineers, and EHS roles across our competitors. The service captured postings consistently and handled duplicates when the same requisition appeared on multiple boards. Skill extraction picked up practical requirements (PLC, SAP, CNC) more often than I expected. A few salary ranges were missing on smaller regional sites, but that’s more about the source data than the pipeline.
Project: Tracked postings across 22 manufacturing employers in three states; nightly sync into our SQL Server reporting database.
★★★★★ 5
Reliable market benchmarking
Our practice advises clients on workforce strategy, so we needed timely job market benchmarking without manual research. AHK.AI set up a scrape schedule that aligned with our weekly refresh and provided normalized titles plus SOC codes for consistent rollups. The employer metadata and industry tagging helped us separate boutique firms from enterprise consultancies. We also appreciated the clean URLs and full descriptions for auditability when a client asked “where did this come from?”
Project: Collected postings from 10 consulting firms and two aggregators; enriched and delivered to BigQuery for dashboards.
★★★★ 4.5
Good data for planning
We analyze hiring across universities and edtech providers to inform program planning. Their pipeline captured faculty, instructional design, and IT roles with consistent formatting. The remote/hybrid/on-site field was especially helpful since many postings bury location details in the description. Dedupe worked well when roles were reposted across campus sites and boards. I’d love slightly more granular employer metadata for multi-campus systems, but overall it’s a dependable feed.
Project: Scraped 50+ university career pages and one higher-ed board; synced enriched records to our internal analytics API.
★★★★★ 5
Fast, accurate job feed
We run a labor market tool for warehousing and last-mile delivery. AHK.AI’s scraping held up against frequent posting changes and aggressive refresh cycles. The standardized titles helped us group “warehouse associate” roles that were labeled a dozen different ways. Skill/stack extraction caught WMS terms and certifications, and the remote/on-site flag was spot on for dispatch vs. corporate roles. The database sync was painless and hasn’t missed a run.
Project: Monitored 14 logistics employers and 3 boards; hourly scraping with dedupe and enrichment into our MySQL database.
