About the job
Join Our Ambitious Team to Shape the Future of Running Training
At Runna, we empower everyday runners to achieve their goals through our cutting-edge app, offering exceptional training, coaching, and a vibrant community for all levels—from improving your 5K time to preparing for your first marathon.
With rapid growth following our recent $6.5M funding round in November 2023, led by JamJar and supported by Eka Ventures, Venrex, and Creator Ventures, we are on an exciting journey. In 2024, we were honored as one of three global finalists for Apple's iPhone App of the Year and were acquired by Strava in 2025!
Our vision is bold: to become the premier global training platform for millions of runners worldwide. We seek passionate individuals to help us create something impactful, especially now with Strava's support propelling our mission forward.
The Team You’ll Be Part Of:
We are on the lookout for a Customer Experience Content & AI Knowledge Specialist to take charge of Runna’s Help Centre and knowledge management processes within our Customer Experience team.
In this role, you will ensure that customers can quickly access clear and accurate information and that our AI systems are supported by well-organized, reliable knowledge. You will set the benchmarks for our published content, ensure its relevance, and develop a knowledge infrastructure that enhances the customer experience.
Your Responsibilities:
Oversee the Help Centre’s App & FAQ section comprehensively—focusing on information architecture, searchability, content quality, and ongoing enhancements.
Craft, refine, and update content that enables customers to confidently self-serve, ensuring clarity, empathy, and excellent support outcomes.
Implement streamlined governance to maintain content accuracy as our product evolves (including ownership, review cycles, verification processes, and change alerts).
Prepare knowledge to be AI-ready—organize and manage content so that our AI tools can efficiently retrieve and deliver accurate responses.
Utilize feedback mechanisms (search queries, contact reasons, article ratings, AI escalations, and agent feedback) to identify gaps and prioritize high-impact improvements.

