Building an AI-Powered Resume and Job Matching Platform

I built a personal project using Next.js, NestJS, PostgreSQL, TypeScript, AWS infrastructure, Docker, Terraform, and LLM-based workflows.

The goal was to create a scalable system for resume optimization, job matching, and AI-generated reporting.

The architecture needed to support frontend, backend, database, cloud deployment, CI/CD, and future AI workflow expansion.

I designed modular APIs, implemented LLM-based workflows, deployed containerized services on AWS ECS and RDS with Docker, ALB, and Terraform, and configured CI/CD using Amplify and GitHub Actions.

The main trade-off was accepting infrastructure complexity to make the platform closer to production-grade architecture rather than keeping it as a simple prototype.

The project demonstrates full-stack, cloud, infrastructure, and AI workflow experience in one cohesive platform.

I learned that AI features should be designed as workflows with data, evaluation, and operational boundaries, not just one-off prompt calls pretending to be architecture.