This repository demonstrates how AI agents can assist in resume tailoring and interview preparation by analyzing job postings, extracting relevant skills, and optimizing application materials. The multi-agent system leverages Amazon Bedrock, and CrewAI to automate resume enhancement and interview readiness.
The system takes in inputs like resumes, GitHub profiles, and personal websites, processes them using AI agents, and produces tailored resumes and interview Q&A to maximize job application success.
- Job Researcher – Extracts key skills and qualifications from job postings.
- Personal Profiler – Analyzes the candidate’s strengths from various online sources.
- Resume Strategist – Customizes resumes based on the extracted insights.
- Interview Coach – Generates key Q&A for interview preparation.
Each agent works in collaboration under a Crew Manager LLM, ensuring a structured workflow.
Before running the code, make sure you have the following set up:
- Serper API Key (or other search APIs):
- Sign up at Serper to obtain an API key.
- Add the key to the
.envfile asSERPER_API_KEY.
To access models on Amazon Bedrock, configure your AWS credentials by running:
aws configureFollow the prompts to enter your AWS Access Key ID, Secret Access Key, Region, and Output format.
git clone https://github.com/viktoriasemaan/multi-agent.git
cd jobhunting-crew- Load job posting details (URL or text)
- Provide your resume, GitHub profile, or personal site
- Agents will analyze and optimize your resume
- Receive a structured resume and interview Q&A
This project is licensed under the MIT License.
Contributions are welcome! Feel free to open issues or submit pull requests to improve the solution.