JobWizard: Your AI Job Seeker

This is a submission for the Bright Data AI Web Access Hackathon

What I Built

JobWizard is an AI-powered web application that transforms the job search process, saving hours of manual effort and boosting application success rates. It automates the discovery of relevant job offers and generates personalized cover letters tailored to each role, using real-time company and user data. Whether you’re a data engineer seeking roles in France or a marketer exploring remote opportunities, JobWizard streamlines your job hunt with precision and speed.

The system addresses the real-world problem of time-consuming job searches and generic applications. By leveraging Bright Data’s MCP server, JobWizard scours the web for up-to-date job listings, enriches them with insights (e.g., company culture, salary ranges), and crafts compelling cover letters that align your skills with employer needs. Built with a custom TypeScript multi-agent framework, JobWizard orchestrates complex workflows to deliver a seamless, human-in-the-loop experience.

Demo

Try JobWizard live at https://brightdata-mcp.bitswired.com

Testing Credentials:

• Email: [e-mail]
• Password: Provided by email to Noah to avoid abuse

Usage Notes:

As a proof-of-concept built under time constraints, JobWizard focuses on demonstrating core functionality rather than handling all corner cases or scalability. To ensure a smooth experience, I recommend selecting 1 or 2 job offers when prompted to choose roles, as this keeps the process quick. The full workflow (resume parsing, job discovery, data enrichment, and cover letter generation) involves extensive scraping with our multi-agent system and Bright Data’s MCP tools, so it may take a few minutes to complete.

Mobile and Desktop Compatibility:

JobWizard works seamlessly on both mobile and desktop, but maintaining the WebSocket connection is critical for the process to complete uninterrupted. On desktop, simply avoid refreshing the page. On mobile, please don’t exit the app or let the phone lock, as this may break the WebSocket connection. Reconnecting after unlocking can disrupt the process. This is a straightforward fix that I can implement, but it wasn’t prioritized for the demo as it adds limited value for showcasing the core functionality.

Repository: https://github.com/bitswired/jobwizard.

Here’s JobWizard in action:

Desktop Demo: Watch JobWizard find “Remote Jobs in AI” and generate a tailored cover letter.

Mobile Demo: Watch JobWizard find “AI Engineers jobs in Geneva” and generate a tailored cover letter.

The demo showcases the full workflow: upload a resume, discover job offers (e.g., “Azure Data Engineer at Devoteam”), select roles, enrich data, and receive a personalized cover letter, all powered by Bright Data’s real-time web data.

How I Used Bright Data's Infrastructure

JobWizard integrates Bright Data’s MCP server to enable robust, real-time web data tasks, fulfilling the challenge’s four key criteria:

• Discover: The agent-offers-finder uses search_engine to query job boards like LinkedIn, BuiltIn, and RemoteRocketship (e.g., “Data engineering jobs in France Python SQL AWS”), finding relevant listings instantly.
• Access: Bright Data’s scrape_as_markdown tool navigates complex, JavaScript-rendered pages (e.g., Devoteam’s career page at https://jobs.smartrecruiters.com/devoteam/744000042826005) without rate limits or IP blocks, ensuring reliable access.
• Extract: The agent-offer-enricher employs scrape_as_markdown and web_data_linkedin_company_profile to pull structured data, such as job requirements and company insights, from dynamic sources.

Bright Data’s infrastructure was critical in overcoming the challenge of scraping accurate data from dynamic websites, which often impose rate limits or IP blocks. Tools like search_engine and scrape_as_markdown simplified access to high-quality, real-time data, enabling JobWizard to deliver precise job matches and enriched insights.

Performance Improvements

Real-time web data access via Bright Data’s MCP server significantly enhances JobWizard’s performance compared to traditional approaches (e.g., static job databases or manual scraping):

• Accuracy: Real-time data ensures job listings are current, avoiding outdated or closed positions. For example, JobWizard pulls live postings from LinkedIn and job boards, improving match relevance.
• Speed: Automated discovery and extraction reduce job search time from hours to minutes. Bright Data’s tools fetch and process data instantly, enabling rapid offer curation.
• Quality: Enriched data (e.g., company culture, salary ranges) grounds cover letter generation in specific, up-to-date insights, producing tailored outputs that resonate with employers. A sample cover letter for an Azure Data Engineer role at Devoteam aligned the user’s AWS experience with the job’s Azure requirements, boosting application impact.
• Reliability: Bright Data’s infrastructure eliminates rate limits and IP blocks, ensuring consistent data access compared to brittle, traditional scraping methods.

By grounding AI performance in reliable, real-time web data, JobWizard delivers a faster, more effective job application process, directly addressing the challenge’s goal of solving real-world problems.

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Acknowledgments:

Huge thanks to Bright Data for their excellent MCP server tools and $250 in credits, which made JobWizard possible. I’ve given their repo a star at github.com/luminati-io/brightdata-mcp 🌟. This was a blast to build!

Contact: Reach out at [e-mail] or X for updates.