Full Stack Developer

Project description:
development of an application to process candidate CVs using AI.

Responsibilities:

• initiated a Proof of Concept (POC) using several low-code platforms such as Illa, AppSmith, and Lowcoder to evaluate their features and team collaboration capabilities;
• created a database in Supabase (which uses postgres) along with buckets for storing various documents and images;
• used Docker to containerize Lowcoder images from Docker Hub, allowing us to work with a specific, stable version of the platform;
• implemented Microsoft OAuth authentication to ensure that only users with a Microsoft Societec account could log in;
• later, rewrote the application in React, TypeScript and NextJS, using Tailwind and CSS for styling, Prettier and ESLint for linting, App Router for navigation, and both Redux and App Context for managing global state;
• used GraphQL services to perform CRUD operations on the Supabase data;
• integrated REST APIs from HuggingFace to extract and synthesize information from candidate PFDs into JSON format;
• used Jira to create tasks and stay on track with deadlines and sprint plans;
• fine-tuned a large language model (LLM) to power a chatbot that could query the database and retrieve candidates based on user-defined requirements;
• implemented data export functionality using predefined PDF templates;
• Vercel was used to deploy the application;
• worked in teams ranging from 2 to 5 people; primarily followed the Feature-Driven Development methodology, but also AGILE practices when working in larger teams;
• used Git and GitHub for code versioning and branching.

Technologies:
Illa, AppSmith, Lowcoder, Docker, Microsoft OAuth, React, TypeScript, NextJS, Tailwind, CSS, Prettier, ESLint, App Router, Redux, App Context, GraphQL, REST, Jira, python, Git, GitHub.