I built Designjobs.careers because I was tired of using job boards that weren't built for designers. Generic platforms lump design roles in with everything else, their filters are useless, and half the listings are either stale or irrelevant. So I built something better.
What is DesignJobs.careers?
It's a job board focused entirely on design roles. Product Design, UI/UX, Graphic Design, UX Research, Brand Design, and more. The filters actually make sense, the listings are relevant, and I'm building features that solve real problems designers face when job hunting. Currently has over 5,500 listings and 1,000+ registered users. The site is live at designjobs.careers.
The platform has grown to over 1,000 registered users, doubling since launch. Weekly active users climbed from around 100 in October to 250-300 by January 2026. Daily active users fluctuate between 20 and 70+ depending on the day, with consistent engagement on job applications.
Direct traffic leads, which makes sense for a job board people bookmark. Google is the second biggest referrer, meaning the SEO work is paying off. But one of the more surprising sources is ChatGPT. Users are asking AI assistants for job board recommendations and getting sent to DesignJobs.careers.
Homepage / Jobs list
Blog page
Building Solo
I built this using Cursor for development and Supabase for the database and authentication. I didn't hand-code every line, but my years of coding experience meant I could read, review, and debug everything being written. When something broke, I knew how to fix it. When the AI-generated code wasn't quite right, I could spot it and correct it. The tools accelerated the build, but the experience made it possible.
Solving Real Problems for Designers
Building a product solo means every decision is yours. What to build, what to skip, what to prioritize. This is where years of collaborating with product managers and thinking beyond the design file pays off. I'm not just shipping features. I'm choosing which problems are worth solving and in what order.
Job matching: Most job boards make you scroll through hundreds of irrelevant listings. The platform analyzes user profiles and skills to surface opportunities that actually fit. Designers see roles that match their experience and what they're looking for.
Resume reports: Applying for jobs and hearing nothing back is demoralizing. Users can get AI-powered feedback on their resumes, analyzed against a specific job. The system breaks down what's working, what's missing, and exactly what to change.
User dashboard: A central place to manage saved jobs, track applications, and view resume reports. Designers can see their job matches, mark roles as applied or not interested, and keep their search organized.
Job description converter: Employers often have job descriptions in messy Word docs with inconsistent formatting. AI converts those raw documents into clean, structured listings, cutting posting time significantly. Less friction for employers means more listings for designers.
Data cleaning: On the backend, AI tidies up scraped job data before it hits the database. It standardizes formats, extracts key information, and ensures listings are consistent and usable. This runs automatically, so the 5,500+ listings stay clean without manual intervention.
Employer posting tools: Companies can list and manage roles directly on the platform.
Salary guides: Help designers understand market rates before applying or negotiating. Also doubles as an SEO play to bring in organic traffic.
AI Job matcher step 1
Resume Report
This feature analyzes a user's resume against a specific job and breaks down what's working, what's missing, and what to fix. I wanted it to feel actionable, not just a score. A few principles guided the design.
Reduce anxiety before adding pressure. The report leads with what you're doing well before showing what needs work. Job searching is already stressful. Starting with strengths gives users a foundation before asking them to fix things.
Make feedback specific. Every issue comes with a suggested change, formatted so it's concrete and easy to act on. "Your resume lacks keywords" is useless. "Add descriptions that include visual storytelling and brand identity" gives you something to actually do.
Prioritize ruthlessly. Feedback is grouped into action required, passed checks, and optional improvements. Users know immediately what's blocking them versus what's nice-to-have. The color coding reinforces this. Red for urgent, yellow for medium, neutral for optional.
Set expectations during the wait. The loading states aren't just spinners. "Analyzing resume..." then "Calculating score..." signals that something meaningful is happening. It gives users a sense of progress rather than leaving them staring at nothing.
The result is a report that feels like advice from someone who actually reviewed your resume for this specific job. Not a generic checklist.
Resume report example
Front-End Details
A few things under the hood:
•Custom component library including a tag input system, modal variants, tooltips, and skeleton loaders. These are reusable across the platform and handle edge cases like keyboard navigation and dark mode.
•Scroll-aware header that hides when scrolling down and reappears when scrolling up, with threshold logic to prevent jitter.
•Staggered animations on page load so elements fade in sequentially rather than all at once.
Small details matter to me. The mobile menu and welcome email show a new quote every day.
What I Learned
AI is incredible for building fast. I used AI tools extensively throughout development, and they accelerated everything from coding to content creation. But here's the thing: AI isn't quite there yet when it comes to design polish.
The micro-interactions, the spacing decisions, the typography choices that make something feel premium versus generic. AI can approximate these, but getting to the level of polish users expect from a well-designed product still takes a designer's eye. I found myself constantly refining what AI produced, adding the finishing touches that make the difference.
That said, the combination of AI speed and design expertise is powerful. I shipped features in days that would have taken weeks before. The key is knowing when to trust the AI and when to override it.
Where I'm Focusing Next
I'm running A/B experiments to optimize conversion, improving SEO to reach more designers, and building out two bigger features: an AI voice assistant for conversational job search and a talent pool so companies can browse designer profiles directly. The goal is to make Designjobs.careers the go-to destination for designers looking for work. Not by being the biggest, but by being the most useful.
