Scraping Engineer

About the Company

At Mercado Libre’s Competitive Intelligence team, we build innovative and scalable solutions using state-of-the-art technologies like GenAI, advanced scrapers, data processing pipelines, and secure data systems.

About the Role

We are looking for an expert in Scraping & Information Security to lead the development of resilient, privacy-first, and AI-powered systems to enhance our strategic intelligence capabilities.

Responsibilities

• Technical Ownership & Vision: Lead the definition and execution of a long-term technical vision for web data extraction and information protection, balancing aggressive innovation with secure and reliable engineering practices.
• Scraping Architecture & Resilience: Design and implement robust and scalable scraping infrastructures to collect unstructured data from a variety of sources. Ensure resilience against anti-bot mechanisms, CAPTCHAs, rate-limiting, and content obfuscation.
• GenAI Integration for Web Intelligence: Leverage GenAI (e.g. LLMs, RAG pipelines, multimodal AI) to extract, interpret, and enrich data from scraped content, including text, images, and structured signals. Promote automation and semantic understanding through AI.
• Information Security by Design: Ensure that all scraping pipelines adhere to privacy, legal, and ethical standards. Build secure data flows and apply best practices in data encryption, access control, and compliance monitoring.
• Cross-Team Collaboration: Work closely with other engineering and data science teams to integrate scraping outputs and AI models into MELI’s competitive intelligence platforms, contributing to business-critical decisions.
• Continuous Monitoring & Anti-Detection Strategy: Establish anti-blocking strategies and observability layers to monitor scraper health, security risks, data freshness, and relevance. Implement anomaly detection and feedback loops for data quality assurance.
• Innovation Culture & Impact at Scale: Lead the development of reusable scraping components and GenAI-enhanced analysis tools to be shared across multiple teams at MELI, fostering a scalable and secure data extraction ecosystem.

Qualifications

• Master’s or PhD in Computer Science, Cybersecurity, Artificial Intelligence, Software Engineering, or a related technical field.

Required Skills

• Proven experience designing and scaling web scraping systems using tools such as Playwright, Puppeteer, Scrapy, Selenium, and rotating proxies.
• Strong experience in bypassing anti-bot protections, browser fingerprinting techniques, JavaScript-rendered content parsing, and CAPTCHA solving frameworks.
• Deep knowledge of GenAI applications in web intelligence: document parsing with LLMs, few shot or zero-shot classification, entity recognition, and content summarization.
• Familiarity with secure architectures, including TLS, OAuth, secrets management, SAST/DAST tools, and vulnerability mitigation in web contexts.
• Fluency in Python; experience with Go, Node.js, or Rust is a plus.
• Knowledge of data lifecycle security, secure data handling policies, and adherence to data governance and compliance standards.
• Strong problem-solving mindset, with a proactive attitude toward threat modeling, risk assessment, and system hardening.
• Experience working with containerized and distributed systems (Docker, Kubernetes), and CI/CD pipelines.
• Excellent communication skills and ability to align technical initiatives with business goals and stakeholder needs.

Pay range and compensation package

[Pay range or salary or compensation]

Equal Opportunity Statement

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