Job offer writing
Produce in 15-30 minutes an attractive, inclusive, and SEO-optimized job offer.
A poorly written job offer can divide qualified applications by 3. Too generic, too technical, too long, involuntary discriminating wording: pitfalls are numerous. AI lets you produce in 15-30 minutes a polished, inclusive offer optimized for Indeed/LinkedIn. This guide presents the workflow that maximizes qualified applications while respecting legal framework (non-discrimination, mandatory pay transparency in EU since 2026).
Step-by-step workflow
Frame the role precisely
Above all: concrete missions, indispensable vs desired skills, team and manager, business context, salary range (mandatory in some EU jurisdictions in 2026).
Identify attractiveness levers
What distinguishes this role? Salary, remote work, impactful project, strong team, technologies, training, mobility? List these differentiators explicitly.
Generate multiple variants
Produce 2-3 different versions: mission focus, team focus, impact focus. A/B testing on Welcome to the Jungle or LinkedIn identifies winners.
Audit for inclusivity and SEO
Verify: gender-neutral wording, no discriminating criteria, keywords candidates actually search (research on job boards).
Validate legal transparency
Mandatory salary mention in several EU countries in 2026, remote work mention, hiring terms. Verify local law compliance before publication.
Copyable prompts
2 tested and optimized prompts. Adapt the bracketed variables [VARIABLE] to your context.
Complete job offer
You're an expert in B2B job offer writing. Write an offer for this role: **Title**: [TITLE] **Company**: [5-LINE DESCRIPTION] **Location**: [CITY / REMOTE] **Contract**: [PERMANENT / FIXED-TERM / FREELANCE] **Salary**: [RANGE] **Benefits**: [LIST] **Main missions**: [LIST] **Required skills**: [LIST] **Profile**: [SENIORITY / EXPERIENCE] Produce: 1. **Catchy title** (max 60 chars, main keyword first, clear hook) 2. **Introduction hook** (3-4 lines, why this role is unique) 3. **Mission**: what the person concretely does (5-7 actionable bullets) 4. **Profile**: required vs desired skills clearly separated 5. **What we offer**: salary, benefits, team, project (3-5 attractiveness levers) 6. **Recruitment process**: clear steps, estimated duration 7. **CTA**: how to apply, contact Gender-neutral language. No discriminating criteria. Inclusive and factual.
Existing offer audit
Audit this job offer: [OFFER] Produce: 1. **Overall score** /100 with 3 reasons 2. **Inclusivity**: risky wording, gender bias, discriminating mentions 3. **Attractiveness**: what attracts or discourages a good candidate? 4. **Clarity**: ambiguities, excessive jargon, vague missions 5. **Job SEO**: present/missing keywords for Indeed/LinkedIn visibility 6. **Compliance**: mandatory mentions (salary, remote, GDPR) present? 7. **Top 5 priority improvements** with proposed rephrasing
Top tools for this use case
Curated selection of the 3 best AI tools for job offer writing.
Why for this use case: Most relevant for clear, inclusive, nuanced offers. Tolerates detailed briefs.
Why for this use case: Good for punchy variants and catchy hooks. Ideal for A/B testing.
Why for this use case: To search in real time what's done on similar offers (competition, trends, market salary ranges).
Estimated ROI
Time saved
70% on writing (15-30 min vs 1-2h)
Quality gain
Native inclusivity, multiple A/B testable variants, optimized job SEO
Stack cost
$20-40/month
Estimates based on 2026 benchmarks and user feedback. Actual ROI depends on your context.
Frequently asked questions
Should salary be displayed in the offer?
In several EU countries since 2026 (transposition of pay transparency directive): mandatory for any job offer. Beyond legal: offers with salary bring 2-3x more qualified applications.
Can AI introduce discriminating biases?
Yes, particularly on gender and age if not piloted. Precautions: explicit prompt ('gender-neutral, no age criterion'), systematic audit before publication, validation by trained HR. High criminal and reputational risk.
How to optimize job SEO?
Three levers: (1) exact title candidates search (e.g., 'Fullstack developer' rather than 'Coding ninja'), (2) industry keywords in description (techs, levels, sectors), (3) clearly indicated location and contract. AI helps identify these keywords via Perplexity.
How many applications to expect per offer?
Very variable: 5-20 for rare profiles (lead tech, senior data scientist), 50-200 for medium profiles, 500+ for junior generalist profiles. A well-written offer multiplies qualified applications by 2-3.