I design the layer between people and AI systems.
Hey, I'm Miguel. Senior Product Designer with 8 years of experience, currently at Workera. In practice, I've operated as the design lead on most of the products I've shipped: setting the research agenda, making structural calls with tech leads and PMs, and owning the work from framing to launch.
Most of my work sits at one specific intersection: an AI model produces an output, a score, a recommendation, an explanation, and my job is to make that output legible, trustworthy, and actionable for the person reading it. That includes designing for when the system is right, when it's uncertain, and when it's wrong, and making sure people have a real way to push back.
Before Workera I worked across fintech and SaaS products. The throughline hasn't changed: take something structurally complex and give people a clear way to act on it.
I run my own user research, work directly with product and engineering to shape decisions rather than just execute them, and I'll hold a position when the evidence backs it up.
Designing for AI output
Presenting probabilistic, generated, or inferred content in a way people understand and trust, failure states included, with a real path to correct them.
Research that becomes product logic
I run the interviews myself, and the findings turn directly into rules and specs, not just a slide deck.
Cross-functional influence, including upward
I work with PM and engineering from the start. When a decision is structural, I'm in the room with tech leads and the CPO while it's being shaped, not receiving the spec after the fact. I've also mentored junior designers earlier in my career and carry that into how I support cross-functional teams now.
Design systems at scale
The patterns that keep a growing product consistent as it adds surfaces, states, and edge cases no one planned for on day one.
Designing across the full assessment experience at an AI-driven skills intelligence platform: results and scoring, feedback during assessment, reassessment flows, and the recommendation layer. The core problem across all of it is the same: an AI system produces scores and inferences, and the person reading them needs to understand and trust the output without accepting it blindly.
Continued as the product matured, shifting toward structural decisions and AI-augmented work. Led the design of the conversational assistant layer, grounding a "make this conversational" brief into a specific architectural call about where the AI lives relative to the data. Owned and scaled the design system. Integrated AI tools directly into the process: Lovable, Bolt, Figma Make, and Claude to prototype faster and get working concepts in front of stakeholders earlier.
Joined to build Bigdata.com from the ground up, a financial intelligence platform for professional investors powered by RavenPack's AI data infrastructure. Designed and shipped the core product from scratch: watchlist creation, file management, email notifications, onboarding, and a React-based mobile app. From no product to a working platform across web and mobile, owning the design end to end across every surface.
Designed desktop and mobile interfaces across the full process: research, wireframes, high-fidelity mockups, and prototypes. Focused on e-learning tools and websites for academic institutions. Mentored three junior designers, coordinating across their projects and helping them build judgment rather than just execute tasks.
Based in Granada, open to remote roles, currently looking for Senior, Staff, or Lead Product Design positions at AI-first companies where designing trust into the product is the core challenge.