Eloquent AI - Senior Software Engineer, Full-Stack
Requirements
• 7+ years of hands-on experience building full-stack production applications. • Proficiency in modern web technologies, including React, TypeScript, and Node.js. • Experience with backend development using Python. • Strong knowledge of cloud infrastructure (AWS, GCP, or Azure) and scalable architectures. • Understanding of AI-powered applications, including LLMs, chat interfaces, and agentic workflows. • Ability to work in a fast-paced, high-autonomy environment, solving complex problems and delivering impact. • Strong collaboration skills, with experience working in cross-functional teams with engineers, designers, and AI researchers. • You have experience building AI-powered applications with LLM integrations. • You’ve worked in high-performance startups or enterprise AI environments. • You have a sharp eye for UI/UX design and have built intuitive, AI-driven interfaces. • You have experience with GraphQL, WebSockets, or real-time data streaming. • You’ve contributed to open-source projects or have built developer tools for AI.
Responsibilities
• As a Full-Stack Engineer at Eloquent AI, you will be at the forefront of building and scaling AI-powered applications, transforming how enterprises interact with intelligent agents. You’ll work across the entire stack, developing high-performance front-end experiences and scalable back-end systems that power real-time AI-driven workflows. • This role requires strong software engineering skills, a deep understanding of full-stack development, and the ability to work in a fast-paced, AI-first environment. You’ll collaborate with engineers, AI researchers, and product teams to build enterprise-grade solutions that enable seamless AI-human interactions. • Design and build full-stack applications that power AI-driven workflows for enterprise users. • Develop high-performance front-end interfaces for AI agent control, monitoring, and visualization. • Build scalable backend services that support real-time AI interactions, knowledge retrieval, and automation. • Optimize AI-powered UIs to ensure seamless and intuitive user experiences. • Work closely with AI researchers and ML engineers to integrate LLMs, Retrieval-Augmented Generation (RAG), and automation into production-ready applications. • Ship robust, minimal-dependency code that performs efficiently in enterprise environments. • Continuously iterate and refine AI-driven products, balancing user needs with technical feasibility.
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