What are the responsibilities and job description for the Lead Software Engineer, Applied AI (Frontend Leading) position at EPAM Systems?
Our Business Technology organization builds secure and intelligent internal platforms that power our global workforce. As a Lead Software Engineer, Applied AI (Frontend Leading) , you will build intuitive, performant user interfaces and frontend integration libraries that make Generative AI (GenAI) and intelligent automation accessible and useful across IT, HR, Finance, Sales, Marketing, and Customer Support. In this role, you will bridge the gap between complex LLM orchestration and enterprise user experience, ensuring our internal teams can seamlessly adopt and trust AI-driven tools. Req.# Responsibilities Design and build end-to-end GenAI-powered applications, emphasizing intuitive web-based UIs and performant client-side API integrations Develop responsive, accessible frontend interfaces using React, TypeScript, or Vue, engineered for streaming responses and low latency Build and maintain a library of reusable frontend components, hooks, and design systems for enterprise GenAI applications Implement LLM-based experiences using frameworks like LangChain or LlamaIndex with leading model providers (OpenAI, Claude, Gemini, etc.) Collaborate closely with designers and product managers to iterate rapidly on novel AI UX patterns (chat assistants, prompt builders, feedback loops) Ensure top-tier security, accessibility (a11y), observability, and test coverage across client-side and full-stack implementations Requirements Frontend Mastery: 5 years of production experience with React, TypeScript, or Vue for enterprise web applications Engineering Seniority: 5-8 years of software engineering experience across the full web stack (frontend UIs, REST APIs, microservices) AI Application Integration: 2 years of experience integrating GenAI features, LLM APIs, and prompt UI patterns into web applications Python & Cloud Services: Strong Python backend development skills and 2 years of experience consuming/building cloud microservices on AWS, Docker, and REST APIs Component Libraries: Proven experience building, documenting, and maintaining reusable component libraries, design systems, and custom hooks Nice to have Conversational UX & Streaming: Real-time streaming UX patterns (SSE/WebSockets), prompt builders, citations, and summary UI components Web Accessibility (a11y): Deep knowledge of WCAG 2.1 AA compliance and accessible UI component architecture LangChain for JavaScript: Client-side or Node.js LangChain, LangGraph, or LlamaIndex orchestration RAG & Vector Search: Familiarity with RAG pipelines, vector search (Pinecone, OpenSearch), and embedding concepts AI Evaluation & UX: Experience with AI evaluation tooling, feedback loops, and guardrails in user interfaces