AI Powered Recruitment Automation

Advanced Middleware Solution for Intelligent Recruitment

This project is an advanced middleware solution designed to bridge the gap between a Salesforce Applicant Tracking System (ATS) and the intelligent capabilities of Azure OpenAI. Its mission is to revolutionize recruitment workflows by automating candidate matching and proposal generation.

The system addresses two key recruitment challenges: Intelligent Candidate Sourcing and Automated Proposal Generation. It automatically analyzes new job vacancies and identifies the best matches from a large candidate database, considering skills, experience, availability, location, and more. For high-potential matches, it dynamically creates personalized proposal texts or adapts resumes—reducing manual recruiter effort and increasing consistency and quality.

The middleware acts as a central hub, coordinating communication between Salesforce, Azure OpenAI, and a vector database for lightning-fast semantic search.

Key Features

The system provides comprehensive AI-powered recruitment automation with advanced matching capabilities and automated proposal generation.

• AI-Powered Job Matching

  Deep semantic analysis of job descriptions and resumes using OpenAI's language models. Supports matching a single job against hundreds of candidates in one request with multi-criteria analysis including skills, experience, geographic proximity, working hours, salary expectations, availability, and past assignments.

• Dynamic Proposal Generation

  Generates tailored proposal texts aligned with each job's unique requirements. Creates personalized proposal texts or adapts resumes for high-potential matches, reducing manual recruiter effort and increasing consistency and quality.

• Scalable Architecture

  Built with FastAPI for smooth integration with Salesforce or other systems. Features asynchronous, containerized architecture built for modern cloud environments with a lightweight web dashboard for monitoring system activity and managing AI instructions.

Technology Stack

A modern stack chosen for performance, scalability, and developer ergonomics:

Backend: Python, FastAPI, Uvicorn
AI & Data Science: Azure OpenAI Service (gpt-4.1, text-embedding-3-small), Pinecone Vector Database, Pydantic, NLTK & Scikit-learn
Database: SQLAlchemy with SQLite
Frontend: HTML, CSS, JavaScript with Jinja2 templating
Deployment: Docker, Git & GitHub, Dotenv

Architectural Design

The system uses a modern, service-oriented architecture for modularity and scalability. The API Gateway (FastAPI) serves as the entry point for all client requests, handling routing, validation, and authentication. The Service Layer includes MatchingService for coordinating matching workflow, OpenAIService for managing Azure OpenAI interactions, VectorDBService for handling vector DB operations via Pinecone, and DocumentProcessor for extracting and cleaning content from various file formats.

The Data Layer consists of Pinecone for storing vectorized resumes and job descriptions, and SQLite for storing persistent app data and assistant instructions. Full asynchronous workflow support enables high-concurrency processing with minimal blocking.