AI-Powered Job Post Generator for Small Businesses

Simplifying hiring for small businesses through AI-powered job post creation

Indeed | 2021-2022 | UX Designer

Vision & OKR Planning, Strategy, Concept, Design workshop facilitation, Research, Cross-functional collaboration, Rapid prototyping, A/B testing

Summary

Designed and validated an AI-powered tool that simplifies job post creation for time-constrained small business employers. The feature increased application volume, improved applicant-employer matching, and was adopted into Indeed’s global job posting flow.

Background

Previously, Indeed attempted to address this by offering AI-generated suggestions at the end of the job posting process. However, research showed that employers rarely engaged with these suggestions after completing all 12 screens. The placement of the feature was too late in the workflow, making it more of an afterthought than a helpful assistant.

Problems

Small business employers often wear many hats—handling day-to-day operations, managing staff, and overseeing customer service—all while trying to grow their business. Hiring is just one of many responsibilities, and writing an effective job post is often deprioritized due to time constraints and limited hiring experience.

My Role

I led the design of a new AI-powered job post creator that simplifies the process from the start.

Based on past user feedback and known drop-off points, I hypothesized that moving AI suggestions to the start of the job post flow would better capture employers’ attention and reduce time-to-post.

5–10 minutes

It takes employers 5–10 minutes to complete posting a job online.

Prototyping & Internal Alignment

I proposed a redesigned experience that proactively generated job posts using AI, allowing employers to simply review and edit rather than write from scratch. I discussed the idea with product managers and aligned on the opportunity to validate it quickly.

I designed and built a prototype that reduced the flow from 12 to 5 screens. This allowed us to demonstrate value early in the process and helped secure buy-in across engineering, data science, and design teams.

The prototype showed promise in reducing friction for employers and served as a foundation for testing.

User Research

I conducted user interviews with a UX researcher to evaluate how employers responded to AI-generated job posts:

Some participants appreciated the time-saving aspect and accepted the AI-suggested content.
Others preferred to tailor content due to specific company needs.

Based on this, I iterated on multiple versions of the prototype to better balance automation and customization.

MVP & Rollout

We launched an A/B test targeting employers who are less familiar with hiring practices. I collaborated with the US job posting team to integrate the AI experience into the main job posting flow while ensuring minimal conflict with existing features.

Impact

Jobs created using the AI feature received significantly more applications.
Employers responded to applicants more frequently, indicating improved candidate-job fit.
There was a measurable increase in job posting completions.
Job posts were generated in under 5 seconds on average.*
The feature contributed to an increase in platform revenue.

*Source

Job Applications

Significant Increase

Responses to Applicants

Significant Increase

Posted Jobs

Significant Increase

Revenue

Significant Increase

Next Steps

Following the MVP, I worked with the US team to simplify and embed the experience into the core product. The AI job post feature now supports employers in writing higher-quality posts faster, helping small businesses compete more effectively in talent acquisition.

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