Explicitly requires vibe coding skills — rapid prototyping with AI-assisted coding tools and LLMs (Cursor, Copilot, Claude Code, ChatGPT) to build agentic architectures and demos.
About the Role
Build rapid prototypes and MVPs of LLM-powered applications using AI-assisted development tools and modern full-stack frameworks. Collaborate with product and UX teams to design APIs, AI agents, and automation workflows that accelerate developer productivity and product experimentation.
Job Description
Role
AI Vibe Coding Engineers at Gruve rapidly transform ideas into working prototypes and lightweight full-stack applications using AI-assisted development tools and LLMs. The role focuses on experimentation, building LLM-powered workflows and agents, and improving developer productivity through automation and AI-native practices.
Key Responsibilities
- Rapidly prototype applications using AI-assisted coding tools.
- Build and iterate on LLM-powered applications, RAG workflows, and AI agents.
- Utilize tools such as Cursor, Claude Code, GitHub Copilot, ChatGPT, Windsurf, and Replit AI.
- Design and integrate MCP servers, APIs, automation workflows, and agentic architectures.
- Develop lightweight full-stack applications using modern frameworks (e.g., React, Next.js).
- Experiment with prompts, embeddings, semantic search, and vector-database-driven workflows.
- Collaborate with product and UX teams to convert ideas into demos and MVPs.
- Improve developer productivity through automation and AI-native workflows.
- Stay current with emerging AI engineering tools, frameworks, and best practices.
Requirements
- Strong programming skills in Python, JavaScript/TypeScript, Node.js, or Golang.
- 1–2 years of experience in vibe coding, rapid prototyping, and working with LLMs/Generative AI.
- Experience with React, Next.js, REST APIs, Git, and GitHub.
- Hands-on use of AI coding assistants such as Cursor, Claude Code, GitHub Copilot, and ChatGPT.
- Understanding of LLMs, prompt engineering, RAG architectures, AI agents, and MCP concepts.
- Strong communication, presentation, problem-solving, and analytical skills.
- Ability to work independently and thrive in a fast-paced remote environment.
Basic Qualifications
- Graduate degree in Computer Science, Software Engineering, Data Science, AI, or a related field.
- Proven ability to turn ideas into working demos quickly (hours or days).
- Self-starter mentality with a focus on experimentation and continuous learning.
Preferred Qualifications
- Experience building GenAI applications, personal projects, or hackathon solutions.
- Familiarity with vector databases, embeddings, and semantic search.
- Exposure to LangChain, LangGraph, CrewAI, AutoGen, or similar frameworks.
- Knowledge of Docker, Kubernetes, and cloud platforms (AWS, Azure, or GCP).
- Experience integrating AI workflows with enterprise applications and a strong product mindset.