UX Designer Resume Checklist

A UX designer CV is evaluated differently to most others. Recruiters aren’t only looking at where you’ve worked — they’re reading for evidence that you can frame problems clearly, collaborate across disciplines, and produce designs that actually move outcomes. This checklist covers every dimension that matters in screening, from portfolio placement to impact framing and ATS compatibility.

What Hiring Managers Scan for in a UX CV

UX hiring managers read CVs with a specific lens. In the first pass, they’re looking for three things:

• Portfolio evidence before anything else. A UX CV without a visible portfolio link in the header is a red flag regardless of experience. Hiring managers expect to click through to case studies. If your portfolio link is buried or missing, many will stop reading before they reach your first role.
• Problem framing, not just execution. The most common mistake on UX CVs is describing what was designed without explaining why. Recruiters want to see that you identified the right problem before designing a solution. A bullet that starts with the discovery — “Following research with 24 users that revealed...” — is fundamentally stronger than one that leads with the deliverable.
• Outcomes, not artefacts. Wireframes, prototypes, and flows are the work — not the result of the work. Every significant project on your CV should include what changed after you shipped: task completion rates, conversion improvements, time-on-task reductions, SUS scores, adoption figures, or NPS shifts. If your bullets only list deliverables, they look like a job description, not an achievement record.

Beyond the first scan, experienced UX interviewers look for research depth (what methods, how rigorous, how many participants), cross-functional evidence (did you work with product, engineering, content, and data — or just hand off to developers?), and systems thinking (have you contributed to or maintained a design system, or designed only one-off screens?).

UX Designer Resume Checklist: 15 Items

• Portfolio URL is in the header, clearly labelled, and live — test it from a different device before submitting any application
• Summary names your seniority, your primary domain (mobile, web app, enterprise SaaS, consumer, regulated industries), and includes one outcome or scale metric
• Each role identifies what type of product you designed for — not just the company name (e.g. “Designed the core scheduling surface for a 200K-user healthcare app”)
• Research methods named where relevant: user interviews, usability testing, contextual inquiry, card sorting, tree testing, diary studies, A/B testing, or unmoderated remote testing — whichever you actually ran
• At least one outcome metric included per significant project: task success rate, time-on-task, conversion, SUS score, error rate, adoption, NPS, or satisfaction score
• Problem framing visible in at least two bullets: show that you identified or validated the problem before designing — not just that you received a brief and executed it
• Collaboration evidence present: product, engineering, content, data, brand, or research partners named in context — not just listed in a skills section
• Design systems or component library contribution mentioned if applicable: tokens, pattern libraries, Storybook integration, documentation, or governance
• Portfolio case studies referenced in relevant bullets for significant projects — “Full case study at [portfolio link]” as a closing line is legitimate and useful
• Tools listed accurately: Figma, Sketch, Miro, Maze, UserZoom, Dovetail, Notion, Zeroheight, FigJam, or whatever you actually use — not a wish list
• No ATS formatting issues: single column, no image or icon-heavy layouts, no text in header/footer boxes, contact info in the document body
• Keywords reflect the target job description: UX research, information architecture, wireframing, prototyping, user flows, usability testing, accessibility, interaction design, design systems, responsive design
• Delivery evidence present: what shipped, when, and at what scale — not just that you contributed to a project
• Seniority progression visible across roles: from execution to research ownership to design leadership, component contribution to system ownership, or individual to team mentorship
• No bullet starts with “Responsible for”, “Helped with”, or “Assisted in” — every bullet opens with a specific action verb that signals clear ownership

Strong UX Experience Bullets

These examples show the standard to aim for across different areas of UX work. Each one frames the problem, names the process, and closes with a measurable outcome.

Common UX CV Mistakes

AI in Design Ops — and the Skills That Remain Defensible

AI is being integrated into design tooling faster than most designers anticipated. Here’s an honest assessment of what’s changing — and the skills worth signalling on your CV because they’re genuinely hard to automate.

• What AI is already doing in design ops. AI tools are now handling significant portions of design ops work: generating UI variations, auto-applying design tokens, producing annotated specs, summarising usability session transcripts, and generating first-pass copy. If your CV only signals execution skills in these areas — “created wireframes”, “produced prototypes” — without evidence of the upstream judgment that directed that work, it looks increasingly replaceable. AI can produce a wireframe. It cannot frame the right problem.
• Problem framing is the most defensible skill in UX right now. The ability to identify which problem is worth solving — before any design work starts — is not something AI can currently do from a brief alone. It requires synthesis of user research, business context, technical constraints, and strategic judgment. CVs that show this clearly — through discovery-led bullets, research that shaped roadmaps, or design decisions that overturned initial briefs — signal the kind of work that AI augments rather than replaces.
• Taste and systems thinking are genuinely hard to replicate. Aesthetic judgment — knowing when a design is clear, when it creates unnecessary cognitive load, when it will fail a particular user group — is pattern recognition built over thousands of hours of user exposure. Similarly, the ability to design a system that scales (not just a set of screens that work today) requires architectural thinking that AI tools currently lack. On your CV, signal both: individual screen craft and system-level contribution.
• Signal leverage, not anxiety. Designers who are visibly comfortable using AI tools to move faster — generating research synthesis, testing layout variations, producing accessible colour systems — stand out positively. A specific mention of AI-assisted research synthesis or AI-generated component suggestions in the context of a real outcome is far more credible than a generic “AI tools” entry in the skills section.