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Senior UI Engineer (React/React Native & AI Development)

a leading AI-powered application development company

📍 Plano, TX🏢 Hybrid💼 Full-Time
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About This Role

Senior UI Engineer – React & AI Development Plano, TX | Full-Time | Hybrid ───────────────────────────────────────── About the Company A leading AI-powered application development company at the forefront of intelligent software innovation, this organization builds next-generation products that blend modern user interfaces with cutting-edge artificial intelligence. Their teams move fast, think boldly, and ship solutions that genuinely change how people interact with technology. If you thrive where frontend craftsmanship meets AI ambition, this is your environment. ───────────────────────────────────────── The Role This is a hands-on engineering role for someone who can do two things exceptionally well: craft polished, scalable user interfaces and wire them directly into the intelligence layer of modern AI applications. You will sit at the intersection of frontend development and applied AI — building experiences that feel seamless to users while being powered by sophisticated language models, agentic workflows, and retrieval systems underneath. This is not a role for someone who wants to specialize narrowly; it rewards engineers who are equally comfortable debating component architecture and tuning a prompt for production accuracy. ───────────────────────────────────────── What You Will Do • Design and build responsive web and mobile interfaces using React.js and React Native, with a focus on reusability, performance, and cross-platform consistency. • Embed AI capabilities — including LLM-powered features, intelligent assistants, and conversational flows — directly into the applications you build. • Craft, iterate, and optimize prompts for large language models to improve output quality and deliver better end-user experiences. • Architect and orchestrate AI agent workflows using frameworks such as LangChain, LangGraph, CrewAI, AutoGen, Semantic Kernel, or comparable tooling. • Implement RAG (Retrieval-Augmented Generation) patterns, working with vector databases and embeddings to ground AI responses in relevant context. • Collaborate closely with product, UX, and backend engineering teams to deliver complete, end-to-end features. • Contribute to architecture reviews, code quality initiatives, and performance optimization across the stack. • Monitor, evaluate, and continuously improve AI-integrated features in production environments. • Keep a close eye on the evolving frontend and AI landscape, bringing forward ideas that keep the product ahead of the curve. ───────────────────────────────────────── What We Are Looking For • Proven hands-on experience with React.js and/or React Native • Strong command of JavaScript (ES6+) and TypeScript • Solid proficiency in HTML5 and CSS3 for cross-platform UI work • Experience with state management approaches including Redux, Zustand, or Context API • Strong Python programming skills for AI and backend integration work • Demonstrated experience with prompt engineering for production LLM applications • Hands-on integration experience with AI services such as OpenAI, Azure OpenAI, Anthropic, or Gemini • Experience building and deploying AI agents and agentic workflow systems • Familiarity with RAG architectures, vector databases, and embedding strategies • Comfort working with REST APIs and modern frontend development conventions The ideal candidate brings a rare combination of frontend depth and applied AI experience. You have shipped React or React Native applications that real users depend on, and you have also built features that call language models, manage context intelligently, and handle the unpredictability that comes with AI-driven systems. Your Python skills let you move fluidly between the UI layer and the AI logic beneath it. You understand that great AI-powered products are not just about model capability — they are about how thoughtfully the interface surfaces that capability to the person using it. ───────────────────────────────────────── Nice to Have • Experience with cloud platforms such as Azure, AWS, or GCP • Familiarity with CI/CD pipelines and DevOps workflows • Background building copilot-style or conversational AI products • Hands-on experience with Docker and Kubernetes • Exposure to Model Context Protocol (MCP) • Experience using AI observability and evaluation tooling • Knowledge of GraphQL and microservices patterns • Mobile app deployment experience across iOS and Android Candidates who have shipped AI-powered conversational or copilot products will stand out — that experience signals an understanding of the full lifecycle, from prompt design through deployment and monitoring. Cloud platform familiarity is a practical advantage given the infrastructure this team works with daily. Exposure to MCP or AI observability tools suggests someone who thinks beyond the happy path and cares about how AI systems behave at scale and over time. ───────────────────────────────────────── What We Offer • Hybrid work model based in Plano, TX, offering flexibility alongside meaningful in-person collaboration • A long-term engagement on a high-impact product with real AI ambition behind it • The opportunity to work at the genuine intersection of modern frontend engineering and applied AI — not as a future roadmap item, but as the core of what you will do every day • Exposure to a fast-moving AI tooling ecosystem, with the autonomy to recommend and adopt emerging technologies • A collaborative team culture that values ownership, technical curiosity, and the ability to bridge disciplines

Required Skills

React.js and/or React NativeJavaScript (ES6+) and TypeScriptPythonPrompt EngineeringLLM integration (OpenAI, Azure OpenAI, Anthropic, Gemini)AI Agent developmentState management (Redux, Zustand, Context API)RAG architecturesREST API integrationAgentic workflow orchestration

Nice to Have

Azure, AWS, or GCP cloud platformsCI/CD pipelines and DevOps practicesAI-powered copilot or conversational application developmentDocker and KubernetesMCP (Model Context Protocol)AI observability toolsGraphQLMicroservices architecturesiOS and Android mobile app deployment
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