JOBMOO

AI-Powered Autonomous Job Hunting Stack

Headline Outcome
"Automated the end-to-end job hunt loop from sourcing to matching to application submission."
ReactExpressMongoDBRedisPlaywrightOpenAI
Jobmoo hero artwork

Case Highlights

"Built a fullstack automation pipeline that compresses the manual job-hunting loop into a managed system."

Project Status

Pending

Project Timeline

2 months

Focused delivery window from planning through core implementation.

The Result

Multi-source
Job Coverage
AI-scored
Fit Prioritization
Queued
Application Pipeline

What This Project Was

JOBMOO was built to reduce the repetitive overhead of searching roles, scoring fit, preparing outreach, and applying across multiple channels. Job seekers often spend more time collecting and filtering opportunities than actually pursuing the best ones. The platform needed to centralize that workflow and keep it visible through a dashboard.

The Main Problem

Job sources expose different formats, rate limits, and interaction models, which makes one unified workflow difficult. On top of that, tailoring applications manually does not scale when a candidate wants to move quickly without sacrificing quality. The system needed to scrape, score, generate materials, and submit actions while keeping progress observable and repeatable.

The Key Turning Point

The most valuable shift was treating job hunting like an automation pipeline rather than a list of one-off tasks. Once jobs become queued records with match scores, generated collateral, and delivery states, the operator can focus on review and strategy instead of repetitive browsing and copying.

What I Built

I implemented a React and Express stack backed by MongoDB, Redis queues, and Playwright automation. The app pulls in opportunities from multiple sources, scores them against a profile, drafts supporting content, and can trigger application actions through supported channels. That turns a fragmented search process into a trackable system with real operational leverage.

1
React Dashboard
2
Express API + Socket Updates
3
MongoDB Record Store
4
Redis/Bull Queue Workloads
5
Playwright Submission Automation

Before vs After

Evaluation MetricBefore ImplementationOptimized Resolution
Opportunity DiscoveryManual site hoppingCentralized automated intake
Application PrepManual tailoring each timeAI-assisted draft generation
Execution VisibilityScattered notesLive dashboard progress

What It Included

Multi-source job scraping across feeds, APIs, and browser automation

AI scoring against candidate profiles with personalized cover letters

Automated application delivery through email and form workflows

Live progress tracking via queues, sockets, and dashboard feedback