AI Skill Report Card

Recruiting Engineers

B+78·Jan 22, 2026

Engineering Recruiting for Startups

1. Write compelling job post focusing on impact and growth
2. Source on GitHub, Stack Overflow, AngelList, referrals
3. Screen with MATCH framework (see below)
4. Technical phone screen → take-home → onsite
5. Check references and close with competitive offer
Recommendation
Add concrete example of a bad MATCH assessment result to show when NOT to advance candidates

Sourcing Phase:

  • Post on startup-focused boards (AngelList, Y Combinator jobs)
  • GitHub search for relevant projects and contributors
  • Stack Overflow talent hunting
  • Employee referral program activation
  • University recruiting (new grad roles)

MATCH Framework Screening:

  • Motivation: Why this role/company? Startup readiness?
  • Ability: Technical skills assessment via coding questions
  • Team fit: Communication style, collaboration examples
  • Culture: Values alignment, work style preferences
  • History: Track record of delivery and growth

Interview Process:

  • 30-min recruiter screen (MATCH framework)
  • 45-min technical phone screen
  • Take-home assignment (2-3 hours max)
  • 4-hour onsite: system design, coding, team interviews
  • Reference checks (2 previous managers)
  • Offer negotiation and close
Recommendation
Include specific templates for reference check questions and offer negotiation scripts

Example 1: Sourcing Message Input: Senior backend engineer for fintech startup Output: "Hi [Name], saw your work on [specific project]. We're a Series A fintech solving [problem] - our backend handles $10M+ daily transactions. Looking for a senior engineer to own our core platform. Interested in a 15-min chat about the role?"

Example 2: MATCH Screening Input: Candidate from big tech wanting startup role MATCH Assessment:

  • Motivation: 8/10 (clear reasons for leaving, excited about ownership)
  • Ability: 9/10 (strong coding, good system design thinking)
  • Team fit: 7/10 (collaborative but used to more structure)
  • Culture: 9/10 (thrives on ambiguity, high ownership)
  • History: 8/10 (shipped features used by millions) Result: Move to technical screen
Recommendation
Provide more detailed sourcing examples with actual GitHub search queries and Stack Overflow techniques
  • Lead with impact in job posts, not just requirements
  • Keep take-homes realistic - respect candidates' time
  • Sell throughout the process - candidates are evaluating you too
  • Move fast - startups lose great candidates to slow processes
  • Check references thoroughly - past performance predicts future
  • Close with urgency but don't pressure unethically
  • Build talent pipeline even when not actively hiring
  • Don't copy big tech interview processes - startups need different signals
  • Don't oversell compensation if equity story isn't compelling yet
  • Don't skip reference checks because you're moving fast
  • Don't ignore culture fit for technical skills - both matter equally
  • Don't make hiring decisions solo - get team input on finalists
  • Don't ghost candidates - startup community is small and reputation matters
0
Grade B+AI Skill Framework
Scorecard
Criteria Breakdown
Quick Start
11/15
Workflow
11/15
Examples
15/20
Completeness
15/20
Format
11/15
Conciseness
11/15