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# AI Vibe Coding Engineer/ GenAI Prototyping Developer

- **Company:** VRN Technologies
- **Location:** United States (Remote available)
- **Experience:** Experienced
- **Contract:** Internship / Graduate position
- **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Applications Architecture, Software Applications, Microsoft Azure, BASIC (Programming Language), Software Quality, Databases, Cursor, Programming Tools, Github, JSON, Python (Programming Language), Node.Js, Open Source Technology, Rapid Prototyping Process, Next.js, Search Technologies, Software Engineering, TypeScript, Web Services, Google Cloud, Enterprise Software Applications, Chatbots, GitHub Copilot, ReactJS, Large Language Models, Multi-Agent Systems, Prompt Engineering, Generative AI, Git, Kubernetes, Restful APIs, GPT, Docker, Web Api, Golang
- **Published:** September 24, 2026
- **Apply:** https://www.dice.com/job-detail/3a59e194-5e65-472b-b507-9e2d9e16cf54

## About the Role

· We are looking for highly motivated and creative AI Vibe Coding Engineer/ GenAI Prototyping Developer with 2-3 years of software development experience to join our innovation-focused engineering team. The ideal candidate is a hands-on builder who is passionate about Generative AI, AI-assisted software development, rapid prototyping, and modern developer tools., · 2-3 years of software development experience, including candidates with strong academic, internship, personal, or open-source project experience.

· Strong programming fundamentals in Python, JavaScript/TypeScript, Node.js, or Golang.

· Basic hands-on experience with React, Next.js, REST APIs, Git, and GitHub.

· Hands-on familiarity with AI-assisted development tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT, Windsurf, or Replit AI.

· Fundamental understanding of Generative AI, LLMs, Prompt Engineering, AI Agents, and RAG.

· Basic understanding of MCP (Model Context Protocol) and how AI agents can interact with tools, APIs, and external systems.

· Exposure to building AI/LLM-based applications, chatbots, workflows, or proof-of-concepts through academic, internship, personal, or open-source projects.

· Understanding of APIs, JSON, web services, and basic application architecture.

· Familiarity with Git-based development and software engineering practices.

· Strong analytical and problem-solving skills with the ability to learn new technologies quickly.

· Strong curiosity and enthusiasm for experimenting with emerging AI tools, frameworks, and developer productivity technologies.

Preferred / Good-to-Have Skills:

· Exposure to LangChain, LangGraph, Crew AI, AutoGen, or similar AI/agent frameworks.

· Familiarity with vector databases, embeddings, semantic search, and RAG implementations.

· Basic exposure to Docker, Kubernetes, AWS, Azure, or Google Cloud Platform.

· Experience integrating AI applications with enterprise systems, databases, or third-party APIs.

· Experience with MCP servers, tool calling, function calling, or agentic workflows.

· Personal projects, GitHub contributions, hackathons, or academic projects involving GenAI, LLMs, or AI agents.

· Ability to use AI coding tools to rapidly convert ideas into functional prototypes or demos.

· Strong product mindset and ability to understand a problem and translate it into a working technical solution.

· Comfortable working in a fast-paced environment involving rapid experimentation, ambiguity, and continuous learning.

· Ability to balance rapid development with code quality, security, maintainability, and engineering best practices.

## Description

· In this role, you will use AI coding assistants such as Cursor, Claude Code, GitHub Copilot, ChatGPT, Windsurf, and similar tools to rapidly transform ideas into functional prototypes, AI-powered applications, internal tools, and proof-of-concepts. You will work with LLMs, AI agents, RAG, MCP servers, APIs, and modern full-stack frameworks, collaborating closely with product, UX, and engineering teams.

· The role is ideal for someone who is curious, comfortable with experimentation and ambiguity, and able to quickly learn and apply emerging AI-native development approaches while maintaining sound software engineering practices.