Technical Talent Screener

Technical Talent Screener: practical plan

Screening design

Competencies

Assess API design, data modeling, debugging, reliability, communication and role motivation. Align each question to actual job responsibilities.

Questions

1. Describe a production service you owned and how you monitored it.
2. Walk through a database change you made safely.
3. Explain how you would investigate a latency regression.
4. Discuss a tradeoff in an API design and its consequences.
5. What support or environment helps you do your best work?

Rubric

Score 1–4 using behaviorally anchored examples: unclear/no evidence, partial understanding, sound approach with evidence, strong reasoning and tradeoff awareness. Allow candidates to ask clarifying questions.

Accessibility and fairness

Share format and duration in advance, offer reasonable accommodations, use the same core questions, and avoid unnecessary personal questions. Do not infer capability from accent, school, employment gaps or interview style alone.

Decision process

Record evidence per competency, discuss with at least two reviewers when feasible, and keep human decision-makers accountable. Validate the screen against job performance over time.

Measurement and review

Record the baseline, source, date range, denominator and owner. Use one primary measure plus quality guardrails; compare like-for-like cohorts and disclose missing data. Treat estimates as scenarios, not observed outcomes.

Risks and controls

Check relevance, consent, disclosure, workload and downside before scaling. Keep an evidence trail, obtain human review for material commitments, and pause if trust, quality or compliance signals deteriorate.

Next steps

1. Confirm the goal, audience and available capacity.
2. Gather the minimum evidence for a first test.
3. Assign an owner, budget and review date.
4. Run a small pilot, record outcomes and decide whether to iterate, expand or stop.