GEO & AI Content Strategist

Role Overview

We are looking for a next-gen wordsmith who understands that traditional keywords are dead and content is only valuable if autonomous AI models can digest and cite it. As our GEO & AI Content Strategist, you will define the synthetic authority voice of FAAZ TECH across our technical journals, enterprise case studies, and modern edge landing pages. You must possess the unique ability to convert raw engineering architectures into high-density semantic narratives that captivate human stakeholders while maximizing citation velocity on ChatGPT, Perplexity, Gemini, and Google SGE.

Key Responsibilities

• Produce high-density, fact-rich articles and insights that position FAAZ TECH as the definitive authority source within AI entity graphs.
• Conduct semantic intent mapping and implement modern Generative Engine Optimization (GEO) parameters (conversational structures, context alignment, and schema compliance).
• Write persuasive, copy matrices for decoupled landing pages and automated conversion funnels that drive high-velocity user action.
• Interview our microservices and WebMCP technical leads to engineer exhaustive case studies that demonstrate structured computational trust.
• Refresh and optimize existing legacy assets to align with autonomous scraper ingestion models and preserve citation velocity over time.
• Collaborate closely with the UI/UX team to ensure that presentation copy and visual data nodes work flawlessly to establish absolute ecosystem credibility.

Requirements

• 2+ years of professional writing experience, specifically tailoring content for high-growth tech firms, deep-tech digital agencies, or B2B SaaS platforms.
• A strong portfolio demonstrating multi-layered writing capabilities—from deep-dive technical breakdowns to punchy conversational product copy.
• Foundational understanding of modern search dynamics, knowledge retrieval metrics, or semantic indexing patterns (familiarity with LLM citation tracking is a massive plus).
• Absolute capability to grasp abstract software engineering metrics (like headless orchestration, real-time edge processing, or RAG loops) and articulate them simply.
• Impeccable structural prose and strict self-editing parameters; you ensure data density without compromising readability.