Publitas turns static, dead PDFs into interactive, shoppable digital content discovery experiences for global brands. Our customers rely on us to stay ahead of the digital curve, and our growth relies on dominating search visibility.
As a freelance SEO/GEO/AEO Specialist, your mission is to build a custom, 24/7 automated competitive intelligence and content engine from scratch. We are not looking for a traditional content writer or a basic keyword researcher who manually uses AI tools. We need a technical builder who sits at the intersection of SEO strategy, web scraping, and LLM orchestration. You will design a proprietary software pipeline that continuously monitors our industry space, catches top competitor moves, and serves up optimized drafts via an automated human-in-the-loop workflow.
We measure engineering talent by architectural execution speed, code quality, and system adaptability. Here is what you will achieve in your first 3 months:
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Day 30: You have mapped out our technical SEO landscape and built the Scraping & Monitoring Bot. The bot runs continuously, tracking our top 20 competitors and target keyword shifts without getting blocked or triggering bot-detection systems.
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Day 60: You have successfully integrated the LLM Pipeline (Claude API). The engine can ingest scraped competitor data, layer in our brand guidelines and USPs, and automatically output structured, high-density, non-commodity content designed to win classic Google links and AI engine citations (GEO/AEO).
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Day 90: You have deployed the Human-in-the-Loop Approval Workflow. The entire engine functions as a "Pull Request" system, staging perfect drafts in our CMS with a seamless one-click review interface for our marketing team. You are now actively iterating on prompts to drive the AI garbage rate to zero.
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Architectural Mindset: You don't just write scripts; you build robust, maintainable data pipelines. You love designing clean workflows, handling API error-catching, and ensuring automations run seamlessly in the background.
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A Continuous Growth Mindset: The search landscape is shifting daily. You treat shifts in search algorithms or generative engines as engineering puzzles to solve, actively updating prompts and data structures so our engine stays ahead.
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Radical Proactivity: In an async team, waiting around to be told what to optimize is fatal. If a scraper breaks or an API updates, you don't wait for a sync meeting—you jump in, debug the script, and deploy the fix yourself.
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Expert Python & Scraping Skills: Deep, demonstrable experience with Python and advanced scraping frameworks (Scrapy, BeautifulSoup, Selenium, or Playwright). You must know how to manage proxy rotation and headless browsers.
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LLM & Prompt Engineering Mastery: Direct experience building production-level workflows with the Anthropic (Claude) and OpenAI APIs, utilizing advanced prompt engineering and RAG data structures.
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Modern Search Architecture (SEO/GEO/AEO): You deeply understand Technical SEO, programmatic SEO frameworks, semantic HTML, and what it takes to optimize content for AI Overviews, ChatGPT, Gemini, and Perplexity citations.
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Pipeline Automation: Experience setting up webhook-driven approval pipelines that push data directly to CMS platforms (Webflow, WordPress, etc.) or trigger developer notifications (Slack, GitHub).
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Flawless Written English: Because we are a fully remote, async-first team, your communication must be exceptional.
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EU Residency & Time Zone Alignment: You must be legally based within the EU to align with our core engineering and delivery cycles.
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Transparent Compensation: A competitive expert-level hourly rate
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True Remote Autonomy: We work 80% asynchronously using Notion and Slack. We don't monitor your screen or count your hours—we trust you to own your engineering targets and manage your day.
At Publitas, we see AI as a core lever for performance, efficiency, and innovation. We expect all team members to actively use AI in their daily work to improve quality, speed, and output.
Depending on the role, this ranges from effectively using AI tools in day-to-day workflows to designing and scaling AI-driven systems. We are not looking for candidates who are “AI-curious”; we look for people who already use AI to do better work and can demonstrate tangible impact.
