Scraping/Antibot engineer

About the role and client:
We are looking for an Scraping Engineer who will design, build, and operate large-scale, resilient web scraping systems, with a focus on Google and Google-like search environments. This role sits at the intersection of data engineering, reverse engineering, and systems reliability, and is critical to delivering accurate, timely, and trustworthy data at scale. Our client is a leader in adopting coding with AI tools. The role is ideal for someone who believes in agentic coding and would like to improve their skills.

Responsibilities:
- Design and maintain large-scale Python scraping systems that operate reliably against Google and other highly defended websites
- Build scrapers for dynamic, JavaScript-heavy pages using browser automation and hybrid approaches
- Continuously adapt to changes in page structure, request flows, and anti-automation mechanisms
- Engineer robust extraction pipelines that prioritise data accuracy, consistency, and observability
- Implement proxy, fingerprinting, and request-routing strategies to maximise stability and throughput
- Monitor scrape health, detect failures early, and rapidly debug production issues
- Optimise performance, cost, and latency across scraping infrastructure
- Work closely with data engineers, data scientists, and product teams to ensure scraped data is usable and trusted
- Document scraping logic and operational runbooks for long-term maintainability

Requirements:
- Professional experience with Python (or another main language, i.e. GoLang, Rust, JavaScript) including production-grade scraping systems
- Experience scraping Google or similarly protected platforms
- Understanding of HTTP, TLS, cookies, headers, redirects, and browser networking behaviour
- Experience with tools such as Playwright, Selenium, Puppeteer, or equivalent browser automation frameworks
- Knowledge of HTML parsing, DOM traversal, and data extraction techniques
- Experience handling rate limiting, CAPTCHA, IP rotation, and bot detection systems
- Comfortable working with asynchronous and concurrent scraping architectures
- Experience running scrapers at scale in cloud environments
- Debugging skills and ability to reason about complex failure modes
- Experience with headless browser fingerprinting and anti-bot evasion techniques

Nice-To-Have:
- Familiarity with containerisation and orchestration, such as Docker and Kubernetes
- Experience with distributed task systems and job queues
- Background in data quality monitoring and anomaly detection
- Experience working with search, advertising, or competitive intelligence data

What the client offers:
- Startup Engineering culture
- Remote working
- Strong Culture
- Award-Winning Product
- Stock Options
- Trust-Based Vacation
- Flexible Work
- Career Growth
- Monthly Hackdays & Training Days
- Family Care Package
- Home Office Stipend
- Swag Welcome Gift
- Birthday Day Off
- Regular Socials
- Volunteer Days