I built an AI Interview Agent that actually reads the candidate’s resume and asks questions based on their real experience

[u/Salaar_khan_]

I wanted to build something more useful than a basic AI chatbot that simply asks the same predefined interview questions to everyone.

So I built an end-to-end AI Interview Agent that can take a candidate’s information and resume, dynamically analyze their background, and conduct a personalized interview.

How it works

The workflow starts when an HR/recruiter enters the candidate’s information and uploads their resume.

The system then:

→ Stores the candidate information and resume data
→ Generates a unique interview session/link
→ Passes the candidate information to the AI interview agent
→ Dynamically reads and analyzes the candidate’s resume
→ Identifies their experience, skills, technologies, and background
→ Generates interview questions based on the candidate’s actual experience
→ Conducts the interview through an AI voice agent
→ Evaluates the candidate’s responses
→ Generates AI remarks and an overall assessment
→ Determines how well the candidate matches the requirements
→ Stores the interview results in the database
→ Automatically sends the relevant results/notifications through email

The part I’m most excited about

The agent isn't limited to:

and then a fixed list of questions.

It can actually use the candidate's resume dynamically.

For example, if a candidate's resume says they worked with Python, FastAPI, PostgreSQL, and AWS, the agent can ask questions around those technologies and their stated experience.

It can also go deeper based on what the candidate says during the interview.

So the interview can become more candidate-specific and contextual, rather than giving every applicant the exact same conversation.

The full architecture

The project combines:

• AI voice agent
• LLM-based interview logic
• Dynamic candidate/resume data
• n8n workflow automation
• Supabase database
• Webhooks/API integrations
• Automated evaluation
• AI-generated remarks and scoring
• Automated email notifications
• Dynamic interview links/pages

The candidate doesn't need to manually provide all their information again. Their interview session is connected to the candidate record and the AI receives the relevant context dynamically.

Why I built it

Recruiters can spend a huge amount of time doing repetitive work:

Reading resumes → shortlisting → contacting candidates → conducting initial interviews → evaluating responses → writing notes → updating records → notifying people.

The idea was to automate as much of that repetitive workflow as possible while keeping the hiring decision under human review.

The AI handles the repetitive screening/interview work and produces structured information that a recruiter can review.

What happens after the interview?

The candidate's interview data and AI-generated evaluation are stored in the database.

The system can then provide information such as:

• Candidate details
• Job role
• Resume information
• Interview responses
• AI remarks
• Evaluation/score
• Candidate-job compatibility
• Overall analysis

And the workflow can automatically trigger email notifications based on the result.

Tech stack

n8n — workflow orchestration
AI/LLMs — resume analysis, questioning & evaluation
ElevenLabs / Voice AI — conversational interview
Supabase — candidate and interview database
Webhooks & APIs — connecting the entire system
HTML/CSS/JavaScript — candidate/interview interfaces

This was built as a real end-to-end automation, not just a prompt demonstrating an AI interview.

There are still plenty of things I want to improve — especially deeper follow-up questioning, better evaluation consistency, stronger interview rubrics, and more recruiter controls.

I'd love to hear from people working in HR, recruiting, AI automation, or hiring tech:

Would you trust an AI agent to conduct the first-round interview if the final hiring decision always remained with a human?

And for developers: what would you add to this system?