Lead Software Engineer, Applied AI (Frontend Leading)

EPAM Systems; New York (NY); On-site; USD 150,000 - 210,000; Full time

Job summary

EPAM Systems in New York seeks a Lead Software Engineer, Applied AI (Frontend Leading) to design and deliver GenAI-powered web UIs and frontend libraries for enterprise use across IT, HR, Finance, and Customer Support. You will bridge GenAI orchestration with smooth UX using React/TypeScript or Vue, building scalable components and reusable libraries for enterprise GenAI apps.

You will advance LLM-based experiences with LangChain or LlamaIndex, ensure performance, accessibility, and security,

Qualifications

• 5+ years of frontend experience in enterprise web apps.
• Experience delivering GenAI-powered UIs and experiences.
• Strong knowledge of React, TypeScript, or Vue.
• Experience with streaming UX and real-time data in web apps.

Responsibilities

• Design and build GenAI-powered frontend interfaces and UI components.
• Develop responsive, accessible frontends with low latency and streaming support.
• Create and maintain a library of reusable components, hooks, and design systems.
• Implement LLM-based experiences using LangChain or similar tools.
• Collaborate with designers and product managers to iterate AI UX patterns.
• Ensure security, accessibility, observability, and test coverage across frontend and full-stack.

Skills

Frontend development

React

TypeScript

Vue

LLM integration

Streaming UI

Web accessibility (a11y)

LangChain / LlamaIndex

REST APIs

AWS / Cloud

Tools

LangChain JavaScript tools

Job description

Our Business Technology organization builds secure and intelligent internal platforms that power our global workforce.

Lead Software Engineer, Applied AI (Frontend Leading)

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.#1090018301

• 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
• 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
• 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