Responsibilities:

📍Architect and maintain automated SEO diagnostic systems using Python and BigQuery to analyze 500K+ pages at scale 📍Develop technical strategies for Generative Search (AI Overviews, ChatGPT, Perplexity) through structured data and programmatic content signals 📍Build and deploy programmatic internal linking systems using SQL and graph-based logic to automate site architecture 📍Create automated content quality assessment workflows using LLM APIs (OpenAI/Anthropic) to identify thin content and cannibalization 📍Build and maintain custom SEO APIs and MCP servers to integrate external datasets with internal LLM-agent workflows 📍Develop Python scripts for high-volume log file analysis, crawl-budget optimization, and rendering diagnostics 📍Engineer SQL-heavy performance dashboards unifying organic traffic, conversion attribution, and competitive positioning 📍Implement complex Schema.org deployments and automated authorship systems within CI/CD pipelines 📍Use algorithmic logic for keyword clustering and intent classification across multi-language datasets 📍Build automated SEO QA frameworks (indexability, hreflang, and core web vitals validation) into the production pipeline

Requirements:

📍5+ years of experience in Software Engineering or Data Engineering with a proven track record of hands-on SEO execution at scale 📍Advanced proficiency in SQL and BigQuery, with specific experience architecting data warehouse solutions for SEO and performance analytics 📍Strong Python programming experience: pandas, scikit-learn, API integrations, web scraping, data pipeline orchestration 📍Deep understanding of LLM architectures, RAG systems, and prompt engineering to build search-optimized workflows and agentic tools

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