Build with the network.

— About the project

We are seeking a Python Engineer to build and scale the data ingestion infrastructure for a global Anti-Money Laundering (AML) and PEP screening platform. The core of our product relies on acquiring highly accurate, up-to-date entity data from hundreds of disparate government watchlists and legal registries worldwide. You will be responsible for developing the data acquisition pipelines — using traditional scraping frameworks combined with cutting-edge agentic AI — to parse unstructured legal texts, press releases, and sanction lists into structured data.

— The role

You will own the extraction process: from writing resilient spiders, to optimizing data cleaning pipelines, to integrating LLMs that can intelligently parse complex biographical and legal information when standard HTML parsing fails.

— Key responsibilities

• Develop Scrapy infrastructure: design, build, and maintain a fleet of Scrapy spiders targeting global government sanctions and watchlist sites.
• Build data pipelines: develop robust Scrapy Item Pipelines to clean, normalize, and deduplicate entity data (names, aliases, birth dates, nationalities) before it reaches the core database.
• AI-driven extraction: integrate OpenAI APIs to parse unstructured text (e.g. unstructured PDF press releases regarding new sanctions) into strict JSON schemas.
• Implement agentic workflows: utilize the Google Antigravity SDK to build autonomous agents that can adapt to changing target website schemas and intelligently manage the extraction lifecycle.
• Circumvent anti-bot systems: implement proxy rotation, custom middlewares, and request throttling to reliably access protected public data sources.

— Required technical skills

• Python proficiency: deep understanding of Python 3.x, object-oriented design, and asynchronous programming.
• Web scraping mastery: extensive experience with Scrapy, including custom middlewares, request throttling, and complex pagination.
• AI/LLM integration: hands-on experience with the OpenAI API (specifically function calling and structured outputs) and modern agentic frameworks like the Antigravity SDK.
• Data quality: a strong engineering mindset focused on data validation, cleaning, and error handling for mission-critical compliance data.

— Nice to have

• Basic familiarity with Docker, containerization, or cloud deployment concepts.
• Familiarity with AML, KYC (Know Your Customer), or PEP screening domains.
• Experience extracting text from complex document formats (PDFs, Word documents) commonly used by government agencies.