Interview scorecard template

IT Recruiter interview scorecard

Pre-screening scorecard for IT Recruiter candidates.

See AI scoring
sales business developmentats workflowboolean sourcingcandidate pipelinetechnical recruiting
Complete evaluation framework

What to assess and how to score it

Review the evidence signals before interviewing. Then use the anchored descriptions—not instinct alone—to choose the score that best matches each answer.

01
Evaluation factor

Track record

35% weight

Check placement numbers for technical roles: requisitions closed per quarter, time to fill for backend or DevOps hires, offer acceptance rate, and named ATS such as Greenhouse or Lever.

Evidence to listen for

  • Gives numbers: quota, attainment, deal size, client roster
  • Explains the market and buyer they sold to, not just the product
  • Distinguishes what they closed from what the team closed
  • Can describe a deal they lost and why

Five-point scoring guide

1
Poor

No numbers; cannot describe what they actually sold or to whom.

2
Needs Improvement

Vague attainment; credit for team results is unclear.

3
Satisfactory

Real record with some numbers; attribution occasionally fuzzy.

4
Very Good

Clear numbers and ownership, including honest losses.

5
Excellent

Quotes concrete figures, for example 14 engineering hires in a year at 32 days average time to fill, with offer accept rate.

02
Evaluation factor

Method and qualification

25% weight

Test sourcing and screening method: Boolean and X-Ray strings, GitHub or Stack Overflow sourcing, intake meetings with hiring managers, and how they judge a Java versus Kotlin CV without being an engineer.

Evidence to listen for

  • Has a repeatable approach to qualifying and progressing deals
  • Can walk a real deal from first contact to close
  • Handles objections with questions rather than scripts
  • Knows when to disqualify

Five-point scoring guide

1
Poor

No method; pitches at everyone and hopes.

2
Needs Improvement

Weak qualification; deals stall with no diagnosis.

3
Satisfactory

Workable method; inconsistent on complex or long cycles.

4
Very Good

Clear repeatable method; disqualifies early and deliberately.

5
Excellent

Describes a repeatable intake and calibration process, shows real search strings, and explains how they screen stacks they cannot code in.

03
Evaluation factor

Relationships and trust

25% weight

Probe how they keep passive senior engineers engaged: follow-up cadence, referral generation, candidate withdrawal recovery, and relationships with hiring managers who reject most of the shortlist.

Evidence to listen for

  • Has clients or talent who came back or referred them
  • Manages a difficult conversation without damaging the relationship
  • Represents the client's interest, not only the commission
  • Builds rapport across seniority levels

Five-point scoring guide

1
Poor

Transactional; burns relationships for a close.

2
Needs Improvement

Builds rapport but does not sustain relationships.

3
Satisfactory

Solid relationships; less tested in conflict.

4
Very Good

Repeat business and referrals; handles conflict without damage.

5
Excellent

Names candidates who returned months later or referred peers, and describes rebuilding trust with a hiring manager after a bad shortlist.

04
Evaluation factor

Drive and resilience

15% weight

Assess response to a frozen requisition, counter-offer losses, and 100 outreach messages returning three replies; look for how they reset targets and rework messaging.

Evidence to listen for

  • Handles rejection and a bad quarter without unravelling
  • Self-directed on pipeline rather than waiting for leads
  • Coachable on feedback
  • Honest in how they represent the product and themselves

Five-point scoring guide

1
Poor

Gives up easily; blames leads, product, or market.

2
Needs Improvement

Motivation depends on momentum; resistant to coaching.

3
Satisfactory

Steady; recovers from setbacks with support.

4
Very Good

Self-motivated, coachable, and steady through bad stretches.

5
Excellent

Treats low reply rates as a messaging problem, tracks outreach conversion, and gives examples of pipelines rebuilt after a lost finalist.

Put this rubric to work

Score every candidate against the same standard

Add these weighted factors to Hirevire and let AI evaluate recorded answers against your rubric.

Explore AI Scorecards