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AI Vibe coding

Amaze Systems IncUnited States🇺🇸United States

Quick overview

SeniorityMid Senior
Work modeHybrid
LocationUnited States
DockerNext.jsGitAWSGoGoogle CloudLLMPythonGenerative AIRESTAzureNode.jsReactKubernetesJavaScriptTypeScriptPrompt EngineeringLangChainLangGraphRAG

Job description

Role : AI Vibe coding
Location : USA PST time zone (Remote / Hybrid ). Time zone to follow: PST
Duration: Long Term Contract
Type of Role: W2
Language: Turkish (Proficient) OR Italian (Proficienct)

Job description :

  • 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, CrewAI, 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.

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