The job description is the first touchpoint between your company and potential candidates. Yet most JDs are riddled with language that inadvertently discourages qualified people from applying.

The Hidden Bias in Job Descriptions

Research from multiple studies reveals alarming patterns:

Gendered language: Words like “ninja”, “rockstar”, “aggressive”, and “dominant” skew male. Words like “nurturing”, “supportive”, and “collaborative” skew female. Both limit your talent pool.
Inflated requirements: “10+ years of experience in a 5-year-old technology” is more common than you’d think. Unnecessary requirements disproportionately deter women and underrepresented groups, who are less likely to apply unless they meet 100% of listed criteria.
Cultural assumptions: Phrases like “beer Fridays”, “fast-paced bro culture”, or “must be a cultural fit” signal exclusion.

How Aram’s JD Generator Works

Our AI-powered JD generator tackles these issues head-on:

Language Analysis

Every generated JD passes through our bias detection engine, which flags:

Gendered terms and suggests neutral alternatives
Aggressive or exclusionary phrasing
Jargon that could confuse candidates from non-traditional backgrounds

Requirement Optimization

The AI distinguishes between must-have and nice-to-have qualifications based on actual role requirements. It prevents requirement inflation by benchmarking against similar roles across industries.

Inclusive Formatting

Our JDs follow best practices for accessibility and inclusion:

Clear, scannable structure
Salary range inclusion (where legally required and recommended)
Explicit diversity and accommodation statements
Remote/hybrid/on-site clarity

Before & After

Before (typical JD):

“We need a rockstar developer who can crush code in a fast-paced environment. 8+ years of React required. Must thrive under pressure.”

After (Aram-generated):

“We’re looking for an experienced frontend developer to help build intuitive user interfaces. Strong React skills preferred (4+ years). We support flexible working arrangements and provide a collaborative, supportive environment.”

Same role. Dramatically different reach.

The Impact

Companies using Aram’s JD generator have seen:

40% increase in applications from underrepresented groups
25% reduction in time-to-fill
Higher quality shortlists due to broader, more diverse applicant pools

Great hiring starts with great job descriptions. Let AI help you get them right.

Building Bias-Free Job Descriptions with AI