Inspiration
The job application process can often be daunting, especially when it comes to optimising resumes for each individual position. As a undergraduate student I have been searching for a side project to sharpen my skills when it clicked that I could help many fellow peers with such a tool. I wanted to create a solution that would simplify the resume-building process and help job seekers and especially other students better tailor their applications to stand out. That’s how JobBot was born.
What it does
JobBot is an AI-powered resume and cover letter chat assistant designed to enhance job applications. Users can upload their resumes and a job description, and JobBot analyses both, providing bullet point suggestions and overall resume structure. The tool suggests modifications, ensuring the user’s resume is aligned with the role they are applying for.
How I built it
I developed JobBot using Java and Spring Boot, integrating the Gemini/Vertex API to power the resume and job description analysis. The front-end is built with Vue.js for a smooth user experience, while the back-end leverages Spring and PostgreSQL to handle requests and data processing. The first version is currently still deployed on www.jobbot.de. I spent countless all nighters to build JobBot during the last year whilst studying and working.
Challenges I ran into
One of the biggest challenges was implementing a useful web socket chat and user flow utilising the Gemini AI to deliver helpful, specific feedback and suggestions without overwhelming users with too many recommendations. Additionally, balancing the front-end’s user-friendly interface with the back-end’s complexity required several iterations. Lastly, I had to ensure the system is secure and the code clean and maintainable.
Accomplishments that I am proud of
I am proud of developing a tool that can assist job seekers in such a tangible way. One of my biggest accomplishments was getting over 100 students to use it and even enable many of them to land their first internships and positions. I also implemented a feedback system that’s not only intuitive but also actionable—users know exactly what to change to make their resumes more competitive. Another highlight was integrating a sleek UI that makes the user experience seamless from start to finish.
What I learned
Throughout the development of JobBot, I learned the importance of user-centric design. I spent a lot of time gathering feedback from testers to make sure our tool was providing value and not just generic advice. Additionally, I learned a great deal about natural language processing and its role in analysing text to derive actionable insights.
What’s next for JobBot
In the future, I plan to enhance JobBot by adding new features such as interview question predictions based on the job description, expanding its support to cover CVs and LinkedIn profiles, and improving the AI’s accuracy in recognising specific industry jargon. We also aim to provide more personalised recommendations and integrate with job
Log in or sign up for Devpost to join the conversation.