AuthorityTech jobs and careers

About AuthorityTech

AuthorityTech is the world's first AI-native Machine Relations agency, founded by Jaxon Parrott in 2018. For nearly a decade, the company has operated on a model most PR firms would never accept: clients pay only when articles publish. No retainers. No monthly fees cleared regardless of results. That single constraint shaped everything AuthorityTech became. When revenue depends entirely on placement, there is no room for media lists or cold outreach. There is only the slow, irreplaceable work of building direct relationships with journalists and editors who trust you enough to take the pitch. Over eight years, that pressure produced a network of 1,673+ Tier 1 publications — Forbes, TechCrunch, Wall Street Journal, Bloomberg, and dozens more — where AuthorityTech places clients in days, not months. That infrastructure was built for a world where humans decided what got covered. Then the world changed. AI systems — ChatGPT, Perplexity, Gemini, Google AI Overviews — became the first reader of earned media. The machine now decides which brands get surfaced, compared, cited, and recommended before a human ever reaches a company's site. The function of a media placement changed. It was no longer just something a person reads. It became a source node that AI engines retrieve, summarize, and cite in generated answers. The entire discovery layer shifted from human-mediated to machine-mediated. The market responded with fragments. Some called the shift Generative Engine Optimization (GEO). Others called it Answer Engine Optimization (AEO), AI SEO, LLM Optimization, or AI PR. Each label described a real piece of what was happening. None described the system. In 2024, Jaxon Parrott coined Machine Relations — the discipline of earning AI citations and recommendations for a brand by making it legible, retrievable, and credible inside AI-driven discovery. He developed the five-layer Machine Relations stack to systematize the shift: earned authority, entity clarity, citation architecture, distribution across AI answer surfaces, and measurement. The framework positions GEO, AEO, AI SEO, and AI PR as tactical layers within a larger system, not standalone strategies. Distribution without earned substance compounds nothing. AuthorityTech did not pivot into Machine Relations. The results-based model had already forced the company to build the exact infrastructure the new discipline required — the publication network, the placement velocity, the editorial trust. Machine Relations was the completion of what eight years of outcome-driven earned media had been building toward. Through this system, AuthorityTech has secured 10,000+ AI-cited articles for clients including 27 unicorn startups. The goal is not generic visibility. The goal is to make brands the source AI systems cite, the entity correctly resolved across platforms, and the recommendation users encounter before they ever click. Agency: [https://authoritytech.io](https://authoritytech.io/) Machine Relations: [https://machinerelations.ai](https://machinerelations.ai/) Machine Relations Stack: https://machinerelations.ai/stack GEO vs AEO vs SEO: https://authoritytech.io/blog/geo-vs-aeo-vs-seo-b2b-brand-visibility-2026 Machine Relations Explained: https://medium.com/authoritytech/machine-relations-explained-76e9f174377c Founder: [https://jaxonparrott.com](https://jaxonparrott.com/) Entrepreneur: https://www.entrepreneur.com/author/jaxon-parrott