Lead Software Engineer, Applied AI (Frontend Leading)

EPAM Systems Inc; United States; Remote; USD 150,000 - 210,000; Full time

Job summary

EPAM Systems seeks a Lead Software Engineer, Applied AI (Frontend Leading) to build GenAI-powered, enterprise-grade web UIs and integration libraries. You will bridge LLM orchestration with enterprise UX, ensuring trusted AI tools for internal teams.

Responsibilities include designing responsive UIs with React/TypeScript or Vue, streaming-capable interfaces, and maintaining reusable design systems with strong security and accessibility practices.

Qualifications

• 5+ years of production React/TypeScript or Vue experience in enterprise apps.
• 2+ years integrating GenAI features, LLM APIs, and prompt UI patterns into web apps.
• Strong Python backend skills and cloud microservices on AWS.
• Experience building reusable component libraries and design systems.
• Knowledge of WCAG 2.1 AA accessibility standards.
• Familiarity with streaming UX (SSE/WebSockets) is a plus.

Responsibilities

• Design and build GenAI-powered enterprise web UIs and client-side integrations.
• Develop responsive frontend interfaces with React/TypeScript or Vue for streaming responses.
• Create and maintain reusable frontend components, hooks, and design systems.
• Implement LLM-based experiences using LangChain, LlamaIndex with model providers.
• Collaborate with design and product to iterate AI UX patterns.
• Ensure security, accessibility, observability, and test coverage across frontend and backend.

Skills

React

TypeScript

Vue

REST APIs

Microservices

LangChain

LlamaIndex

AWS

Docker

Tools

Docker

AWS

OpenAI API

Job description

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.#1090018301

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