Chief Full Stack Software Engineer

EPAM Systems; Deutschland; Hybrid; EUR 120.000 - 160.000; Vollzeit

Zusammenfassung

EPAM Systems is seeking a Chief Full Stack Software Engineer to deliver fast, intuitive GenAI-powered web interfaces and integration libraries. You will build reusable frontend foundations and connect streaming AI experiences to APIs and microservices across business teams.

You will architect end-to-end GenAI apps, design responsive UIs, and implement LLM-driven journeys with LangChain or LlamaIndex using OpenAI, Claude, or Gemini.

Qualifikationen

• 7+ years delivering production enterprise apps with modern frontend frameworks (React/TypeScript/Vue).
• 7+ years full-stack experience 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; experience with Docker and REST APIs.
• Proficient English, B2+ level or higher.

Aufgaben

• Architect and deliver end-to-end GenAI applications with fast client-side API integrations.
• Design responsive, accessible frontend experiences for streaming outputs and low-latency interactions.
• Build and maintain reusable component libraries, hooks, and design systems for enterprise GenAI apps.
• Implement LLM-driven user journeys using LangChain or LlamaIndex with OpenAI, Claude, or Gemini.
• Collaborate with designers and product managers to iterate on AI UX patterns like chat assistants and prompt builders.
• Ensure security, accessibility, observability, and testing across client-side and full-stack work.
• Create performant UIs for AI interactions including streaming text, prompts, citations, and summaries.
• Maintain a shared library of reusable frontend components and hooks for GenAI capabilities.

Kenntnisse

React

TypeScript

Vue.js

REST APIs

Microservices

GenAI features

LLM APIs

English B2+

Tools

AWS

Docker

Node.js

LangChain

OpenAI APIs

Jobbeschreibung

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

Responsibilities

• Architect and deliver end-to-end GenAI applications, emphasizing intuitive web UIs and fast client-side API integrations
• Design responsive and accessible frontend experiences built 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 using LangChain or LlamaIndex with OpenAI, Claude, or Gemini
• Collaborate with designers and product managers to iterate quickly on AI UX patterns such as chat assistants, prompt builders, and feedback loops
• Ensure security, accessibility, observability, and comprehensive testing across client-side and full-stack work
• Create responsive, accessible, high-performance web UIs for AI interactions including streaming text, prompt inputs, citations, and summaries
• Maintain a shared library of reusable frontend components and hooks so teams can embed GenAI capabilities into their applications
• Develop UI components that improve transparency, observability, and trust in AI-generated outputs

Requirements

• Extensive experience of 7+ years delivering production enterprise apps with React, TypeScript, or Vue
• Proven full-stack background of 7+ years across frontend UIs, REST APIs, and microservices
• Hands-on experience of 3+ years embedding GenAI features, LLM APIs, and prompt UI patterns in web applications
• Solid Python backend skills, plus 3+ years building and consuming cloud microservices on AWS, Docker, and REST APIs
• Demonstrated ability to build, document, and maintain reusable component libraries, design systems, and custom hooks
• English proficiency at a B2+ level or higher

Nice to have

• 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