Anti-Bot Engineer, Adthena

• The role is ideal for someone who believes in agentic coding and would like to improve their skills
• Research shows men apply if they meet ~60% of the criteria, while women and underrepresented groups apply only if they meet all requirements. If you have the skills but don't meet every requirement, reach out – we'd love to explore how you could be a great fit!
• Strong professional experience with Python (or another main language, i.e. GoLang, Rust, JavaScript) including production-grade scraping systems
• Deep hands-on experience scraping Google or similarly protected platforms
• Solid understanding of HTTP, TLS, cookies, headers, redirects, and browser networking behaviour
• Experience with tools such as Playwright, Selenium, Puppeteer, or equivalent browser automation frameworks
• Strong 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
• Strong debugging skills and ability to reason about complex failure modes
• Experience with headless browser fingerprinting and anti-bot evasion techniques
• Pragmatic problem-solving in hostile and fast-changing technical environments
• High ownership of systems that run continuously and at scale
• A strong bias toward reliability, correctness, and observability
• Ability to explain complex technical behaviour clearly to non-specialists
• Curiosity about how large platforms evolve their defences and infrastructure

Desirable

• As an Anti-Bot Engineer, you will design, build, and operate large-scale, resilient web scraping systems, with a strong 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
• You will work on complex scraping problems where naïve approaches do not work, including dynamic rendering, anti-bot defences, frequent markup changes, and high-volume data collection
• We are leaders in adopting coding with AI tools
• 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
• You’ll work closely with:
• Paul Felby, Chief Product & Tech Officer & Ivan Nikolov, Lead Technical Architect

• Interviews: 2 Stages