NextRole

Autonomous Agents 💻 Python ⚖️ MIT 🟢 Actively maintained
49 stars

NextRole is a GenAI-powered career advancement tool that automates interview preparation. It takes your CV and a job description, then uses a multi-agent system to produce a tailored resume PDF, an interview prep document, and a day-of battlecard cheat sheet. It is for developers and professionals who want to streamline job applications and interview prep.

NextRole: AI Agents That Tailor Your Resume & Prep You for Interviews (Demo)

🎬 NextRole: AI Agents That Tailor Your Resume & Prep You for Interviews (Demo) · Tam Nguyen

NextRole demo
🖼️ Screenshot from the project README

✨ Key features

  • Tailored resume PDF via rendercv
  • Deep company and role research
  • Structured interview prep with STAR stories
  • Day-of battlecard PDF cheat sheet
  • Time-boxed prep plans (1 month, 2 weeks, 3 hours)
  • Multi-turn chat for iterative edits

🎯 Use cases

  • Tailor your resume for a specific job application
  • Prepare for an interview with company research and coaching
  • Create a quick reference cheat sheet for interview day
  • Plan your interview prep over a specific timeline

📦 Installation

🧰 Requirements: Requires Docker, API keys for OpenAI, Tavily, and LlamaCloud (or alternative providers), and optionally AWS credentials for Bedrock.

1. Clone & configure
git clone https://github.com/tam159/next-role.git
cd next-role
cp .env.example .env          # then fill in your API keys (see table below)
2. Launch everything
docker compose up -d
3. Find your host ports (set in .env, vary per machine)
docker ps                     # read the 0.0.0.0:<host>->... mappings

🚀 Usage

# After installation, open the frontend UI and follow the in-app instructions.
# Upload your CV and a job description (or JD URL), set your prep timeline, and let the agents work.
# You can also configure your LLM models in the app's Configuration dialog.

❓ FAQ

What do I need to run NextRole?

You need Docker, API keys for OpenAI, Tavily, and LlamaCloud (or alternative providers), and optionally AWS credentials for Bedrock.

Can I use free or local LLMs?

Yes, you can use Google AI Studio's free tier for Gemini models, or point OPENAI_API_BASE to LM Studio or Ollama for fully local models.

How do I change the LLM model?

Open the in-app Configuration dialog and set the main agent and subagent models to a provider:model string (e.g., anthropic:claude-sonnet-5).

What is the shell-command approval feature?

Risky execute commands pause in the UI for approval; a read-only allowlist auto-approves trivial commands. It is on by default and can be disabled via CAREER_AGENT_EXECUTE_APPROVAL=false.

📊 Repository

Stars★ 49
Forks🍴 10
Open issues🐛 6
Last commit🕒 Sep 4, 2026
Created📅 Apr 2026
Language💻 Python
License⚖️ MIT

🤖 Overview, features, install steps and FAQ were generated from the project's README on Sep 4, 2026. Always check the original source before running commands.