Chief Full-Stack Software Engineer

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

Job summary

EPAM Systems in the United States seeks a Chief Full-Stack Software Engineer to craft fast, intuitive GenAI-enabled web interfaces and integration libraries. You will build reusable UI foundations and connect streaming AI experiences to APIs and microservices across business teams.

Lead end-to-end GenAI applications, enforce accessibility and security, and mentor teams while delivering scalable frontend architectures with React, TypeScript, and Vue.

Qualifications

• 7+ years of delivering production enterprise apps using React, TypeScript or Vue.
• 7+ years of full-stack development across frontend UIs, REST APIs and microservices.
• 3+ years embedding GenAI features, LLM APIs, and prompt UI patterns in web apps.
• 3+ years building and consuming cloud microservices on AWS, Docker, and REST APIs.
• Experience building and maintaining reusable component libraries, design systems and hooks.
• Proficiency in English at a B2+ level or higher.
• Nice to have real-time streaming UX patterns (SSE/WebSockets) and WCAG 2.1 AA accessibility.

Responsibilities

• Architect and deliver GenAI applications with intuitive UIs and fast client-side integrations.
• Design responsive, accessible frontend experiences for streaming outputs and low-latency interactions.
• Build and maintain reusable UI components, hooks, and design systems for enterprise GenAI apps.
• Implement LLM-driven user journeys using LangChain or LlamaIndex with OpenAI/Claude/Gemini.
• Partner with designers and product managers to iterate on AI UX patterns like chat assistants and prompts.

Skills

React

TypeScript

Vue

REST APIs

Microservices

GenAI features

LLM APIs

Prompt UI patterns

English communication

Tools

AWS

Docker

OpenAI APIs

LangChain / LlamaIndex

WebSockets / SSE

Job description

We are seeking a Chief Full-Stack Software Engineer to craft intuitive, high-speed web interfaces and integration libraries for GenAI and smart automation. You will develop reusable UI foundations and link streaming AI experiences to APIs and microservices across business teams.

Responsibilities

Architect and deliver end-to-end GenAI applications, prioritizing intuitive web UIs and fast client-side API integrations Design responsive and accessible frontend experiences crafted for streaming outputs and low-latency interactions Build and maintain reusable component libraries, hooks, and design systems for enterprise GenAI applications Implement LLM-driven user journeys leveraging LangChain or LlamaIndex with OpenAI, Claude, or Gemini Partner with designers and product managers to iterate quickly on AI UX patterns such as chat assistants, prompt builders, and feedback loops Guarantee security, accessibility, observability, and comprehensive testing across client-side and full-stack work Craft responsive, accessible, high-performance web UIs for AI interactions including streaming text, prompt inputs, citations, and summaries Sustain a shared library of reusable frontend components and hooks so teams can embed GenAI capabilities into their applications Develop UI components that boost transparency, observability, and trust in AI-generated outputs

Requirements

Background in delivering production enterprise apps with React, TypeScript, or Vue for 7+ years Expertise in full-stack development spanning frontend UIs, REST APIs, and microservices across 7+ years Proficiency in embedding GenAI features, LLM APIs, and prompt UI patterns in web applications for 3+ years Skills in Python backend development, plus 3+ years building and consuming cloud microservices on AWS, Docker, and REST APIs Showcase of building, documenting, and maintaining reusable component libraries, design systems, and custom hooks Proficiency in English at a B2+ level or higher Nice to have Familiarity with real-time streaming UX patterns, covering SSE/WebSockets, prompt builders, citations, and summary UI components Understanding of WCAG 2.1 AA compliance and approaches to designing accessible UI components Competency in client-side or Node.js LangChain, LangGraph, or LlamaIndex orchestration Knowledge of RAG pipelines, vector search platforms such as Pinecone or OpenSearch, and embedding fundamentals Qualifications in AI evaluation tools, feedback loop design, and interface-level guardrails