Background

The world is rapidly changing and the job market is no exception, with the future of work becoming increasingly dependent on digital skills. Unfortunately, young people are struggling to keep up and are three times more likely to be unemployed compared to other age groups, leading to long-lasting impacts on their careers and financial stability. To address...

Core Responsibilities

• Rapid Prototyping & Production Build: Use Lovable to generate production-ready React/Supabase applications from natural language prompts, rapidly iterating on UI/UX and database schemas.
• LLM Strategy & Integration (Claude): Serve as the subject matter expert on Anthropic’s Claude models (Sonnet 3.5, Opus). Design prompts and system instructions that optimize Claude’s reasoning for our specific business logic
• Hybrid Development: Recognize the limits of AI generation. Step in with Scripting (Python/TypeScript) to handle complex edge cases, backend logic, and API integrations that AI tools cannot yet perfect on their own.
• System Architecture: Design the data flow between our frontend apps (Lovable- generated), our backend databases (Supabase/PostgreSQL), and our AI Agents. Ensure security, scalability, and maintainability of AI-generated codebases.
• Workflow Optimization: Build internal tools and scripts that automate the “last mile” of development, connecting our AI apps to external APIs, CI/CD pipelines, and cloud infrastructure.
• Bring new perspectives that challenge assumptions and add original thinking.
• Ensure approaches align with organizational goals before execution.

Technical Requirements

AI & LLM Expertise (The Brains)

• Deep experience with Claude: Proven ability to use Claude 3.5 Sonnet/Opus for code generation and complex reasoning tasks.
• Prompt Engineering: Mastery of “System Prompts” and context window management. You know how to structure a prompt to get clean, bug-free JSON or code output from an LLM.
• Agentic Workflows: Understanding of how to chain LLM calls together to solve multi- step problems.

Application Development (The Build)

• Lovable / V0 / Cursor Mastery: Hands-on experience with AI-native build tools. You specifically know how to drive Lovable.dev to create complex, multi-page applications with authentication and database connections.
• Full Stack Fundamentals: Even though AI writes the code, you must understand React, Tailwind CSS, and Node.js to debug and refactor what the AI produces.
• Database Design: Proficiency with Supabase or PostgreSQL. You can define schemas, Row Level Security (RLS) policies, and relationships that an AI tool can implement.

Scripting & Automation (The Glue)

• Proficient in Python: For backend data processing, RAG (Retrieval Augmented Generation) pipelines, and server-side logic.
• TypeScript/JavaScript: For client-side logic customization within generated apps.
• API Orchestration: Experience connecting REST and GraphQL APIs.

Key Tech Stack

• AI Models: Anthropic Claude 3.5 Sonnet (Primary), GPT-4o.
• Gen-AI Tools: Lovable.dev (Required), Cursor IDE, V0.
• Backend: Supabase, PostgreSQL, Python (FastAPI/Flask).
• Frontend: React, TypeScript, Tailwind CSS.

• Rapid Prototyping & Production Build: Use Lovable to generate production-ready React/Supabase applications from natural language prompts, rapidly iterating on UI/UX and database schemas.
• LLM Strategy & Integration (Claude): Serve as the subject matter expert on Anthropic’s Claude models (Sonnet 3.5, Opus). Design prompts and system instructions that optimize Claude’s reasoning for our specific business logic
• Hybrid Development: Recognize the limits of AI generation. Step in with Scripting (Python/TypeScript) to handle complex edge cases, backend logic, and API integrations that AI tools cannot yet perfect on their own.
• System Architecture: Design the data flow between our frontend apps (Lovable- generated), our backend databases (Supabase/PostgreSQL), and our AI Agents. Ensure security, scalability, and maintainability of AI-generated codebases.
• Workflow Optimization: Build internal tools and scripts that automate the “last mile” of development, connecting our AI apps to external APIs, CI/CD pipelines, and cloud infrastructure.
• Bring new perspectives that challenge assumptions and add original thinking.
• Ensure approaches align with organizational goals before execution.

• Deep experience with Claude: Proven ability to use Claude 3.5 Sonnet/Opus for code generation and complex reasoning tasks.
• Prompt Engineering: Mastery of “System Prompts” and context window management. You know how to structure a prompt to get clean, bug-free JSON or code output from an LLM.
• Agentic Workflows: Understanding of how to chain LLM calls together to solve multi- step problems.
• Lovable / V0 / Cursor Mastery: Hands-on experience with AI-native build tools. You specifically know how to drive Lovable.dev to create complex, multi-page applications with authentication and database connections.
• Full Stack Fundamentals: Even though AI writes the code, you must understand React, Tailwind CSS, and Node.js to debug and refactor what the AI produces.
• Database Design: Proficiency with Supabase or PostgreSQL. You can define schemas, Row Level Security (RLS) policies, and relationships that an AI tool can implement.
• Proficient in Python: For backend data processing, RAG (Retrieval Augmented Generation) pipelines, and server-side logic.
• TypeScript/JavaScript: For client-side logic customization within generated apps.
• API Orchestration: Experience connecting REST and GraphQL APIs.

• Deep experience with Claude: Proven ability to use Claude 3.5 Sonnet/Opus for code generation and complex reasoning tasks.
• Prompt Engineering: Mastery of “System Prompts” and context window management. You know how to structure a prompt to get clean, bug-free JSON or code output from an LLM.
• Agentic Workflows: Understanding of how to chain LLM calls together to solve multi- step problems.
• Lovable / V0 / Cursor Mastery: Hands-on experience with AI-native build tools. You specifically know how to drive Lovable.dev to create complex, multi-page applications with authentication and database connections.
• Full Stack Fundamentals: Even though AI writes the code, you must understand React, Tailwind CSS, and Node.js to debug and refactor what the AI produces.
• Database Design: Proficiency with Supabase or PostgreSQL. You can define schemas, Row Level Security (RLS) policies, and relationships that an AI tool can implement.
• Proficient in Python: For backend data processing, RAG (Retrieval Augmented Generation) pipelines, and server-side logic.
• TypeScript/JavaScript: For client-side logic customization within generated apps.
• API Orchestration: Experience connecting REST and GraphQL APIs.