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In today's competitive job market, the difference between landing an interview or being left behind often lies in a resume's ability to reflect exactly what recruiters are looking for. Inspired by this need, a developer built a tool that analyzes resumes against hundreds of real job postings in the AI sector using artificial intelligence. The project, known as Resume Brutalizer, was born from personal frustration after receiving generic advice from ATS systems that didn't align with the specific requirements of job openings. Instead of passively waiting for an opportunity, he decided to create a solution that identified skill gaps and generated a personalized learning roadmap.
The technical architecture combines a modern frontend with React 19, TypeScript and Tailwind CSS, while the backend relies on Express.js, Node.js and tRPC for efficient client-server communication. The MySQL database, orchestrated with Drizzle ORM, stores more than 215 real job postings extracted from corporate portals, LinkedIn, GitHub and other sources. For resume processing, the Google Gemini API was integrated, which extracts skills structured into categories such as programming languages, frameworks, databases, AI/ML technologies and cloud platforms. This approach not only identifies gaps, but also offers training recommendations aligned with market demand.
One of the biggest challenges was prompt engineering. The first iterations yielded inconsistent results; it was necessary to design very detailed instructions that forced the AI to return a structured JSON by category. This process, known as prompt engineering, proved crucial for achieving accuracy and scalability. Additionally, early deployment on Google Cloud Run revealed database optimization and usability issues that didn't appear in local testing, underscoring the importance of launching minimum viable products as soon as possible.
Beyond the code, this project demonstrates how artificial intelligence can be applied to everyday recruitment problems. Companies looking for AI for businesses can find in similar tools a path to optimize their recruitment processes. For example, integrating AI agents capable of analyzing profiles and suggesting improvements represents a natural evolution of traditional talent management systems.
The project's author learned that starting with a real problem —not with a technology— keeps motivation high and guides technical decisions. He also discovered that documenting the code and gathering early feedback from real users enhances the quality of the final product. Small adjustments to the format of the recommendations improved clarity by 50% according to initial tests. These lessons are applicable to any custom software development, where constant iteration and active listening to the client make the difference.
Looking ahead, plans include expanding the database to more than 500 job postings, incorporating AI interview preparation, salary insights by skill and curated learning resources. Adding cybersecurity features to protect candidates' sensitive data is also being considered, a critical aspect when handling personal documents. The versatility of the stack allows horizontal scaling using aws and azure cloud services, ensuring high availability and performance on demand.
In the analytics field, business intelligence service tools such as Power BI could be integrated to visualize labor market trends: which skills are on the rise, what salaries are associated with each tech stack or how requirements evolve by sector. This would turn the project into a complete data-driven career guidance platform.
Building an AI resume analyzer not only strengthens technical skills in full-stack development, prompt engineering and DevOps, but also demonstrates a problem-solving mindset that recruiters highly value. As the creator says: 'Your next job may be just one project away'. In an ecosystem where custom application development is becoming increasingly relevant, initiatives like this show how technology can bridge the gap between talent and opportunities.
