Hiring the right person for an IT or cybersecurity role is harder than it looks. Most resume screeners are generic — they don't know the difference between what a SOC analyst needs versus a penetration tester, and they definitely can't tell you why a candidate might fail a technical interview three rounds in.
This tool was built to fix that. Upload a resume, select the role you're hiring for, and get a full AI-powered breakdown in seconds — scores, skill gaps, red flags, improvement suggestions, suggested interview questions, and a final hire/reject decision backed by reasoning.
When you upload a resume, the app runs it through LLaMA 3.3 70B via Groq's API. The AI evaluates the candidate specifically for the role you selected — not generically. A penetration tester gets judged on Metasploit and OSCP. An AI/ML engineer gets judged on PyTorch and model evaluation. Every role has its own scoring weights.
Here's what you get back:
- Overall score with a gauge showing hire/review/reject zone
- 6-dimension breakdown — Technical Skills, Cybersecurity Relevance, Experience, Education, Soft Skills, ATS Compatibility
- Radar chart comparing the candidate against industry averages
- Skills audit — what they have, what they're missing, what certifications they should get
- Strengths and weaknesses referenced directly to resume content, not generic observations
- Improvement plan with HIGH / MEDIUM / LOW priority action items
- 3 suggested interview questions targeting the specific gaps found
- Final decision — HIRE, MAYBE, or REJECT — with a confidence score and written reasoning
- Downloadable report in
.txtor.jsonformat
The app currently evaluates candidates for 7 IT and cybersecurity roles, each with its own required skills, preferred skills, and scoring weights:
| Role | Focus |
|---|---|
| 🔴 Penetration Tester / Ethical Hacker | Offensive security, exploit dev, bug bounty |
| 🔵 Security Analyst (SOC / DFIR) | SIEM, incident response, threat hunting |
| 🟢 DevSecOps Engineer | CI/CD security, containers, cloud pipelines |
| 🟡 Full Stack Developer (Security-Focused) | Secure coding, REST APIs, frontend + backend |
| 🤖 AI / ML Engineer | PyTorch, model evaluation, MLOps, LLMs |
| 🌐 Network Security Engineer | Firewalls, VPN, routing, IDS/IPS |
| ☁️ Cloud Security Engineer | AWS/Azure/GCP, IAM, CSPM, compliance |
1. Clone the repo
git clone https://github.com/Tktirth/ai-resume-analyser.git
cd ai-resume-analyser2. Install dependencies
pip install -r requirements.txt3. Add your Groq API key
Create a .env file in the root folder:
GROQ_API_KEY=gsk_your_key_here
You can get a free API key at console.groq.com. No credit card required.
4. Run the app
streamlit run app.pyOpen http://localhost:8501 and you're good to go.
If you want to host it publicly:
- Push this repo to your GitHub account
- Go to share.streamlit.io and sign in with GitHub
- Click New app → select this repo → set main file to
app.py - Open Advanced settings → Secrets and add:
GROQ_API_KEY = "gsk_your_key_here"- Hit Deploy — it'll be live in 2-3 minutes
This project ships as a single file for simplicity. Everything — the parser, AI engine, charts, and UI — lives in app.py.
ai-resume-analyser/
├── app.py # Everything in one file
├── requirements.txt # Python dependencies
├── .env.example # API key template
├── .gitignore
└── .streamlit/
└── config.toml # Dark theme configuration
| What | How |
|---|---|
| UI | Streamlit |
| AI Model | LLaMA 3.3 70B Versatile via Groq API |
| PDF parsing | pdfplumber |
| DOCX parsing | python-docx |
| Charts | Plotly |
| Env management | python-dotenv |
- Scanned PDFs won't work. The parser reads text directly from the file. If someone submitted a photo of their resume exported as PDF, it'll come back empty. They need to provide a text-based PDF.
- Resume length matters. The app sends up to 7,000 characters to the AI. Very long resumes get trimmed. Most standard resumes are well within this limit.
- AI is not infallible. The hire/reject recommendation is a starting point, not a final answer. Always have a human review before making a real hiring call.
I built this as part of my portfolio while studying IT at GTU. The idea came from wanting to build something that sits at the intersection of AI, cybersecurity, and real-world HR workflows — not another CRUD app or weather dashboard.
The AI persona used in the prompts is "Dr. Alexandra Reid" — a fictional senior HR analyst with 20 years of cybersecurity hiring experience at firms like CrowdStrike and Palo Alto Networks. This gives the model a concrete evaluation frame rather than producing vague, generic output.
Tirth — Third year IT undergrad at Gujarat Technological University
Certified in Ethical Hacking from IIT Delhi · Pursuing AI/ML from IIT Guwahati
GitHub: @Tktirth
MIT — use it, modify it, build on it. Just don't use it to make hiring decisions without a human in the loop.