Job Search System
Beginner explanation
A job search system is a repeatable workflow for turning your portfolio into interviews. It is more effective than occasional applications and generic resumes.
Production explanation
For AI engineering roles, the system should connect role targeting, public proof of work, tailored project narratives, and a weekly outreach cadence. The portfolio and the search process should reinforce each other.
Real-world example
A candidate targets AI platform, ML application, and staff-level full-stack AI roles. They use this playbook’s projects to tailor resume bullets, GitHub highlights, and interview stories.
Weekly system
- Refine one public artifact.
- Apply to a focused role set.
- Publish one technical note or demo clip.
- Reach out to two relevant people with specific project context.
- Capture feedback and update the portfolio story.
Mini exercise
Write three role-aligned headlines for the same portfolio: AI product engineer, AI platform engineer, and full-stack AI engineer.
Project assignment
Choose one project and write the exact resume bullet, GitHub summary, and interview story you would use for it.
Interview questions
- Which project best supports the role you want next?
- How do you explain business value, not just implementation detail?
- Which failures or tradeoffs from your project make the strongest interview stories?
Monetization angle
Even if the goal is employment first, the same portfolio assets used in a job search can later support consulting, teaching, or product sales.