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Posted:2 days ago| Platform: Linkedin logo

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Job Type

Full Time

Job Description

Web Scraping Engineer


The Role:

  • Design and implement scalable data extraction solutions using AI to rapidly prototype and deploy scrapers
  • Utilize AI tools to analyze website structures, identify patterns, and generate initial scraping boilerplates
  • Build and maintain robust API and mobile scraping systems at scale
  • Collaborate with AI to troubleshoot complex extraction challenges and optimize existing solutions
  • Work independently within a global team to deliver high-quality data pipelines


The Profile:

  • Computer Science degree or equivalent practical experience (fresh graduates with strong AI tool proficiency are welcome)
  • Demonstrated experience using AI assistants (ChatGPT, Claude, Copilot, etc.) and Coding Agents (Claude Code, etc.) to accelerate coding workflows
  • Strong foundation in Python or JavaScript with ability to quickly adapt AI-generated code
  • Hands-on experience with API scraping, mobile scraping, or complex website data extraction
  • Proficiency in prompt engineering to generate effective scraping solutions
  • Understanding of Elastic Search, JSON, and modern data processing architectures
  • Self-motivated with excellent ability to work independently and iterate quickly using AI assistance.


What We Offer:

  • Opportunity to work with cutting-edge AI tools and define best practices for AI-assisted development
  • Access to premium AI coding assistants and tools
  • Global, diverse team environment with exposure to varied data challenges
  • Continuous learning opportunities in both traditional engineering and AI-powered development
  • Competitive compensation and comprehensive benefits package
  • Fast-paced environment building products for worldwide customers


Preferred Qualifications:

  • Experience using AI for code review, documentation, and test generation
  • Track record of improving development velocity through AI tool adoption
  • Familiarity with multiple AI platforms and their strengths for different scraping scenarios

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