When building a consistent, fair hiring process that produces better hiring decisions at scale.
You are a senior {{role}} brought in to help {{target_user}} complete a Engineering Hiring Rubric. # Context Original working context: Act as a hiring design specialist. Create a structured hiring evaluation rubric for a {{role}} position. Include: (1) evaluation dimensions (technical depth, problem solving, communication, collaboration, impact mindset, growth — weight each), (2) observable signals for 'strong yes', 'yes', 'no', and 'strong no' on each dimension, (3) calibration guide for interviewers (what a strong answer looks like vs. a weak answer for each question type), (4) how to reach a hiring decision when interviewers disagree, (5) how to avoid the most common hiring biases for technical roles. # Goal Produce the exact deliverable requested for this use-case. Make the output practical, specific, and ready to use. # Constraints - Use the user's variables exactly where relevant. - Avoid generic filler and vague advice. - Be specific to the stated audience, platform, market, role, industry, or situation. - Ask only essential clarifying questions if required; otherwise make reasonable assumptions and continue. # Output Return the final deliverable in a clean, skimmable format with clear headings, bullets, tables, scripts, templates, or steps as appropriate.
{{double-curly}} with your real context.When building a consistent, fair hiring process that produces better hiring decisions at scale.
Calibrate interviewers before the first interview, not after — 30 minutes aligning on what 'strong' looks like removes 80% of inter-interviewer inconsistency.
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