Your tasks
We are looking for a "Vibe Coder" - an AI-Native Engineer who has moved beyond traditional syntax-heavy programming to master the art of AI-assisted and autonomous engineering.
You will not just be writing code; you will be orchestrating it. Your primary skill is not how fast you can type Python or JavaScript, but how effectively you can guide State-of-the-Art (SOTA) LLMs to build complex, scalable, and bug-free systems at 10x the speed of a traditional developer. You understand that in this new era, natural language is the new programming language.
Key Responsibilities
• High-Velocity Prototyping: Go from "idea" to "deployed MVP" in hours, not weeks, using AI-native IDEs (Cursor, Windsurf) and cloud
environments (e.g. Replit).
• Agentic Orchestration: Build and manage autonomous AI agents
(using frameworks like LangChain, AutoGen, or custom scripts) to
handle multi-step engineering tasks.
• Architectural Stewardship: Since the AI writes the implementation,
your focus shifts to system design, data structures, and ensuring the
pieces fit together logically.
• "Vibe" Management (Prompt Engineering): Craft precise, contextheavy prompts to guide LLMs toward specific outcomes, managing the context window" effectively.
• Code Review & Security: Act as the rigorous gatekeeper for AIgenerated code. You must be able to read code faster than you write it, spotting hallucinations, security vulnerabilities, and logic errors
instantly.
The "New" Tech Stack (Requirements)
• AI-Native IDE Mastery: Deep proficiency with Cursor or Windsurf. You should know how to use these tools to index codebases and context switch effectively.
• LLM Fluency: You know the "vibes" of different models - when to use
Claude 3.5 Sonnet for coding logic vs. GPT-4o for reasoning.
• Frontend Generation: Experience with generative UI tools to rapidly
scaffold interfaces.
• Agentic Frameworks: Familiarity with building or using agentic loops
(Devin, OpenHands, or simpler RAG pipelines).
• Polyglot Reading Ability: You may not write every language fluently, but you must be able to read and debug multiple languages (Python, TypeScript, Rust, Go) when the AI generates them.
You will not just be writing code; you will be orchestrating it. Your primary skill is not how fast you can type Python or JavaScript, but how effectively you can guide State-of-the-Art (SOTA) LLMs to build complex, scalable, and bug-free systems at 10x the speed of a traditional developer. You understand that in this new era, natural language is the new programming language.
Key Responsibilities
• High-Velocity Prototyping: Go from "idea" to "deployed MVP" in hours, not weeks, using AI-native IDEs (Cursor, Windsurf) and cloud
environments (e.g. Replit).
• Agentic Orchestration: Build and manage autonomous AI agents
(using frameworks like LangChain, AutoGen, or custom scripts) to
handle multi-step engineering tasks.
• Architectural Stewardship: Since the AI writes the implementation,
your focus shifts to system design, data structures, and ensuring the
pieces fit together logically.
• "Vibe" Management (Prompt Engineering): Craft precise, contextheavy prompts to guide LLMs toward specific outcomes, managing the context window" effectively.
• Code Review & Security: Act as the rigorous gatekeeper for AIgenerated code. You must be able to read code faster than you write it, spotting hallucinations, security vulnerabilities, and logic errors
instantly.
The "New" Tech Stack (Requirements)
• AI-Native IDE Mastery: Deep proficiency with Cursor or Windsurf. You should know how to use these tools to index codebases and context switch effectively.
• LLM Fluency: You know the "vibes" of different models - when to use
Claude 3.5 Sonnet for coding logic vs. GPT-4o for reasoning.
• Frontend Generation: Experience with generative UI tools to rapidly
scaffold interfaces.
• Agentic Frameworks: Familiarity with building or using agentic loops
(Devin, OpenHands, or simpler RAG pipelines).
• Polyglot Reading Ability: You may not write every language fluently, but you must be able to read and debug multiple languages (Python, TypeScript, Rust, Go) when the AI generates them.