About Me
I grew up surrounded by music. Some of my earliest memories are of dancing in our living room while my mother worked through a stack of Madonna albums, picking the right track for the right moment on her radio show. She curated playlists for a local station long before the word "playlist" existed. Years later, without deliberately planning it, I found myself doing exactly that at Amazon Music, just for 100 million listeners globally. The obsession with getting it right for the listener never changed. Only the engineering complexity and the scale did.
That customer obsession has followed me across more than a decade of building products. At Amazon, I led mission-critical AI products across four teams and 40+ people spanning San Francisco, Seattle, and Berlin driving engagement, growth, operational efficiency, and cost optimization. Before that I led product initiatives at CoachHub, DKB, and Adidas Runtastic always grounded in the same question: does this create real value, or just the appearance of it?
For the last five years, I've worked exclusively in AI. Not only as an enthusiast, but hands-on, alongside teams training models and building large-scale systems. I've seen where models perform well and where they quietly fail, how bias emerges, and what it takes to make AI reliable under real constraints.
I came to technology deliberately, through curiosity and a growing obsession with what it could make possible. Earning my place in technical conversations taught me something more valuable than any single skill: how to build bridges. Between engineers and executives, between what's technically feasible and what's commercially necessary. My academic studies have sharpened my business lens, so now transformer models and CAPEX feel equally familiar to me.
I work with teams to identify where AI can create real leverage, pressure-test assumptions, align stakeholders, and shape solutions that stand up both technically and commercially. My approach combines strategic clarity with execution discipline, drawing on mechanisms such as working backwards, hypothesis-driven roadmapping, clear success metrics, and operational rigor. I like ambition. I just prefer it with a business case.
When I'm not deep in an AI strategy or a client workshop, you'll probably find me somewhere outside hiking, skiing, played padel, forcing myself away from screens and recharging.
If we haven't already, I'd love to connect.