Nathan Emmons

About Nathan Emmons

I’m a UX Writer and Technical Content Strategist with a passion for designing intuitive content experiences that bridge human understanding and complex AI systems. With a multidisciplinary background in English, technical writing, and theatre, I bring a rare blend of analytical precision, creative clarity, and empathy to every project. At Microsoft, Salesforce, and Google (via Monks), I’ve led content programs for enterprise software, AI tools, and LLMs — specializing in user-focused docs, scalable prompt engineering, and seamless collaboration across design, engineering, and product. My strengths lie in simplifying complexity, aligning content with product strategy, and optimizing content systems for discoverability, clarity, and performance. Key focus areas- UX writing for AI and SaaS platforms (Search Ads, Office Suite, Slack integrations)- LLM training: prompt design, taxonomy, and evaluation frameworks - Data-informed documentation strategy (Power BI, user feedback loops)- Scalable content systems and CMS management (Confluence, WordPress)- Cybersecurity-informed communication for high-trust environments I’m driven by curiosity, creativity, and values-centered leadership, and I thrive in spaces where collaboration, DEI, and purposeful impact are core to the mission. Let’s connect — I’m open to opportunities in UX content, AI writing, and technical strategy roles that empower innovation and clarity at scale.

Experience

1. Ux Ai Writer Prompt Engineering & Llm Training

   Monks

   Jul 2024 — Present · Seattle, WA, US

   Design and write UX content for Google’s ad creation and optimization workflows, translating complex functionality into clear, actionable microcopy that improves user outcomes- Collaborate cross-functionally with designers, PMs, and engineers to create intuitive, user-first experiences at scale- Crafted high-impact prompts to improve the relevance and accuracy of Google’s LLM-powered ad search experience, refining AI behavior through real-world inputs and use cases- Evaluate LLM-generated responses using custom scoring frameworks to ensure accuracy, tone, and usability- Define scalable content taxonomies and terminology libraries for consistency across AI systems and user interfaces- Conduct A/B testing and leverage usage data to refine copy and improve engagement KPIs.

Education

• Reed College

  Bachelor of Arts - BA

  1995 — 1999

• Humboldt State University

  Single Subject Credential

  2009 — 2010

• University of Washington

  Certificate

  2020 — 2021

• Southern Oregon University

  Master of Arts

  2014 — 2016

• University of Delaware

  MFA

  2004 — 2007