ProRecruiter

My Role: Backend & Data Pipeline Developer

Technologies

Project Overview

This project is an AI-based social media recruiting agency platform designed to automate the process of creating recruitment ads and funnel pages. Users provide details about their company in a simple and intuitive way, and the system generates optimized content—including images, text, and layouts—using AI. The platform helps businesses reach potential candidates more effectively while optimizing ad performance through automation.

My Role

As one of the two developers in this project, I was responsible for designing and implementing the entire backend and data pipeline. This included setting up the infrastructure for generating content using AI, managing data flows, and ensuring efficient execution of tasks. Additionally, I contributed to defining the overall architecture and integrating AI-powered features into the system.

Technical Project Description

The platform is built using modern web and AI technologies, with a focus on automation and performance optimization. The key components include:

• Backend & Database:
  • Built using Supabase, which serves as the backend and database solution for authentication and data storage.
  • Prisma ORM was used for structured database management.
• AI-Powered Ad Generation:
  • Uses OpenAI and Together AI models to generate text and images for ads.
  • LangChain facilitates the orchestration of AI workflows and integrations.
• Automated Pipelines:
  • Prefect is used for scheduling and orchestrating AI-based content generation processes.
  • Ensures that ads are continuously optimized based on user engagement and feedback.
• Frontend:
  • Built with Next.js and React for a responsive and interactive user experience.
  • Allows users to input company details and preview generated ads before publishing.
• Performance Optimization:
  • Ad optimization mechanisms ensure that the best-performing variations are identified and deployed automatically.
  • AI-based feedback loops refine the generated content over time.

Challenges

• Ensuring High-Quality AI-Generated Content:
  • AI-generated text and images needed to be relevant and engaging for recruiting campaigns.
  • Implemented multiple refinement steps to enhance the quality of output.
• Scalability & Performance:
  • The system had to handle multiple concurrent users and large-scale ad campaigns efficiently.
  • Used Prefect to distribute and parallelize task execution.
• Real-Time Ad Optimization:
  • Implemented automated A/B testing to measure and improve ad effectiveness dynamically.
• Data Handling & Security:
  • Supabase was chosen for its robust authentication and role-based access controls.
  • Ensured compliance with data privacy regulations when processing user-provided company information.

Achievements

• Fully Automated Ad Creation:
  • Users can generate professional-quality social media ads with minimal effort.
  • The system creates engaging content that is optimized for social media platforms.
• Optimized AI Pipelines:
  • Prefect-based workflow automation ensures efficient content generation and processing.
  • Parallelized AI tasks lead to faster turnaround times for ad generation.
• AI-Driven Performance Improvements:
  • Ads are continuously refined using machine learning-based feedback loops.
  • Automated A/B testing maximizes ad conversion rates.
• User-Friendly Experience:
  • Simple input mechanism allows users to generate high-quality recruiting ads effortlessly.
  • Next.js frontend provides a fast and interactive interface.

Current Status

The platform is currently in active development as a hobby project with two developers and one marketing expert. The core functionalities are in place, and further refinements are being made to enhance ad optimization, content quality, and user engagement. Future iterations may include additional AI-driven insights and deeper integrations with ad platforms for automated deployment and monitoring.