AI Web Scraping Engineer (Stealth Data Acquisition)

Workana•Denver, CO

12d•Remote

About The Position

As an AI Web Scraping Engineer (Stealth Data Acquisition), you will be responsible for designing, building, and maintaining resilient, undetectable data collection systems at scale. This is not a "requests + BeautifulSoup" role — we need someone who has operated against modern anti-bot infrastructure (Cloudflare, PerimeterX, DataDome, Akamai, Kasada) and knows how to stay under the radar while extracting structured data reliably and continuously. You will integrate AI/LLM-based parsing to handle dynamic, unstructured, or frequently-changing page layouts and build self-healing scrapers that detect layout/DOM changes and adapt automatically.

Requirements

4+ years building production web scraping systems at scale (not just scripts — real infrastructure).
Deep hands-on experience with headless browser automation (Playwright, Puppeteer, Selenium) including stealth plugins/patches.
Practical experience defeating or working around Cloudflare, DataDome, PerimeterX, Akamai Bot Manager, Kasada, or similar.
Strong understanding of TLS fingerprinting, HTTP/2 fingerprinting, canvas/WebGL fingerprinting, and browser fingerprint spoofing.
Experience with residential/mobile/datacenter proxy rotation and session management at scale.
Proficiency in Python and/or Node.js/TypeScript for scraping and orchestration.
Experience using LLMs/AI models for content extraction, parsing, and classification on messy/unstructured HTML.
Familiarity with CAPTCHA-solving approaches and detection-avoidance strategies.
Must be based in and authorized to work in the United States.
Must pass a standard background check prior to start.
Comfortable working in a fast-moving, iterative environment where target sites change defenses frequently.

Nice To Haves

Experience with mobile app API reverse engineering (in addition to web).
Background in adversarial ML or anti-bot research (from either side).
Experience with distributed task queues (Celery, Kafka, SQS) for scraping orchestration.
Prior work in a data-as-a-service, alt-data, or web intelligence company.

Responsibilities

Design, build, and maintain stealth-based scraping pipelines that evade bot detection, fingerprinting, and rate-limiting defenses.
Reverse-engineer target sites' anti-automation measures (TLS/JA3 fingerprinting, canvas/WebGL fingerprinting, behavioral detection) and build countermeasures.
Architect distributed scraping infrastructure using rotating residential/mobile proxies, headless browser farms, and session/cookie management at scale.
Integrate AI/LLM-based parsing to handle dynamic, unstructured, or frequently-changing page layouts without brittle selectors.
Build self-healing scrapers that detect layout/DOM changes and adapt automatically.
Monitor scraper health, success rates, and detection signals; rapidly iterate when sites patch defenses.
Ensure data pipelines are compliant with client-defined legal and ethical guardrails (ToS review, robots.txt handling, rate limiting) as directed by Pinwheel's legal/compliance team.
Collaborate with data engineering to deliver clean, structured, deduplicated datasets into downstream systems.