About the role
ExpertVoice Inc - Frontend / AI Engineer All Jobs > Frontend / AI Engineer ExpertVoice Inc Apply Frontend / AI Engineer Remote Worker - N/A • ProdDev Apply Job Type Full-time Description Frontend / AI Engineer Remote, Continental United States About Expertvoice We work with hundreds of the world’s most respected consumer brands – companies like Garmin, Carhartt, Ariat, TaylorMade, Brooks, and more, as well as retailers – to engage influential everyday experts, and to build, track and reward their helpful expertise. At ExpertVoice, we are proud to have cultivated a community of individuals who embody our core values. ExpertVoice employees are authentic, driven, bold and give a damn. We believe that our people are the heart and soul of our organization and their commitment to these values are what drives our success. When you join ExpertVoice, you become part of a team that is united by a shared passion for excellence and a desire to make an impact. Summary We’re looking for a curious and creative Frontend / AI Engineer to help build next-generation AI-powered product experiences. You’ll work closely with our product and engineering teams to turn large language models (LLMs) into real, user-facing features. This role blends front-end development, API integration, and rapid prototyping—perfect for someone eager to explore how AI can transform modern applications. Key
Responsibilities You don’t need a deep AI or machine learning background — just a strong engineering foundation, a maker’s mindset, and a passion for experimenting with new tools and technologies. Build AI-driven product features that integrate LLMs (like GPT, Claude, or Gemini) via APIs Prototype quickly and iterate fast, turning rough concepts into working interfaces and tools Develop front-end experiences in React that make complex AI outputs intuitive and delightful Collaborate with backend engineers to design APIs and data pipelines that support AI interactions Work across the stack when needed — from front-end interfaces to backend service integration in Python Experiment with new LLM capabilities, libraries, and prompt engineering approaches Contribute to internal tools for data cleaning, model evaluation, and content generation workflows