What are the responsibilities and job description for the Full-Stack Engineer position at Confidential Company?
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
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Full-stack development in dev tooling and applications for GenAI copilots & agents
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Spearheading the development and maintenance of high-quality web front-end using React.js
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Contributing to the backend API system for cloud or on-prem deployment
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Staying updated on emerging technologies and best practices in web development
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Wearing many hats and collaborating with Nexusflow.ai’s full team for product development, deployment and customer success
Qualifications
Required
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3 years experience in full-stack web development
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Frontend
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Proficient in developing web applications using React.js, Next.js, TypeScript, and Tailwind CSS.
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Experience with Next.js for server-side rendering and routing.
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Strong understanding of HTML, CSS, and JavaScript.
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Knowledge of state management libraries like Redux.
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Backend
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Experience with backend API system development & deployment on cloud (e.g. AWS).
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Passion for application & platform systems involving ML models, data pipeline and applications.
Preferred
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Work experience in fast-pace teams.
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Experience in building ML applications or ML platforms.
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Experience in projects involving LLMs.
