Full-Stack Engineer

About Nexusflow.ai Modern enterprise copilots & agents call for last-mile quality, enterprise-grade robustness and scalable operation costs, beyond simplified programming interfaces for generative AI. Nexusflow tackles this challenge, enabling enterprises to own their workflow copilots & agents stacked on top of powerful yet cost-effective, compact LLMs. We train large language models and build last-mile quality dev tooling for copilots & agents on your enterprise workflows. Our team has built the open-source LLM, NexusRaven-V2, rivaling GPT-4 in function calling with a 100X smaller model size. Our team members are also behind the scenes of Starling, the #1 ranked compact 7B chat model based on human evaluation in Chatbot Arena. Position: Full-Stack Engineer Nexusflow is currently adding Full-Stack Engineers to our team. Our full-stack engineers are responsible for packaging up our technology in models and last-mile quality toolings as systems. Our full-stack engineers will be the driving force building our products and solutions in extensive collaboration with our ML engineers, designers & our customers. Responsibilities Full-stack development in dev tooling and applications for GenAI copilots & agents Spearheading the development and maintenance of high-quality web front-end using React.js Contributing to the backend API system for cloud or on-prem deployment Staying updated on emerging technologies and best practices in web development Wearing many hats and collaborating with Nexusflow.ai’s full team for product development, deployment and customer success Qualifications Required 3+ years experience in full-stack web development Frontend Proficient in developing web applications using React.js, Next.js, TypeScript, and Tailwind CSS. Experience with Next.js for server-side rendering and routing. Strong understanding of HTML, CSS, and JavaScript. Knowledge of state management libraries like Redux. Backend Experience with backend API system development & deployment on cloud (e.g. AWS). Passion for application & platform systems involving ML models, data pipeline and applications. Preferred Work experience in fast-pace teams. Experience in building ML applications or ML platforms. Experience in projects involving LLMs.

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