Lead Full Stack Software Engineer

We're looking for a Lead Full Stack Software Engineer to create user-friendly, high-performing interfaces and frontend integration libraries that bring GenAI and intelligent automation capabilities to teams across IT, HR, Finance, Sales, Marketing, and Customer Support.

Architect and develop complete GenAI-powered applications, with a focus on intuitive web-based UIs and high-performing client-side API integrations Craft responsive, accessible frontend interfaces designed for streaming responses and minimal latency Construct and sustain a library of reusable frontend components, hooks, and design systems for enterprise-grade GenAI applications Bring LLM-based experiences to life using frameworks such as LangChain or LlamaIndex paired with OpenAI, Claude, or Gemini Partner with designers and product managers to quickly iterate on innovative AI UX patterns, including chat assistants, prompt builders, and feedback loops Guarantee security, accessibility, observability, and thorough test coverage throughout client-side and full-stack builds Produce responsive, accessible, and high-performance web UIs suited to AI-driven interactions like streaming text, prompt inputs, citations, and summaries Sustain a shared library of reusable frontend components and hooks so internal teams can easily integrate GenAI capabilities into their own applications Build UI components that offer transparency, observability, and trust in AI-generated outputs 5+ years building production applications with React, TypeScript, or Vue for enterprise use cases 5–8 years of full-stack software engineering experience spanning frontend UIs, REST APIs, and microservices 2+ years integrating GenAI features, LLM APIs, and prompt UI patterns into web-based applications Solid Python backend skills, along with 2+ years building and consuming cloud microservices on AWS, Docker, and REST APIs Demonstrated track record building, documenting, and maintaining reusable component libraries, design systems, and custom hooks English proficiency at a B2+ level or higher Experience with real-time streaming UX patterns, including SSE/WebSockets, prompt builders, citations, and summary UI components Understanding of WCAG 2.1 AA compliance and how to architect accessible UI components Hands-on skills with client-side or Node.js LangChain, LangGraph, or LlamaIndex orchestration Exposure to RAG pipelines, vector search platforms like Pinecone or OpenSearch, and embedding fundamentals Experience with AI evaluation tools, feedback loop design, and interface-level guardrails