Today we announced that former Amazon and Spotify VP Jay Richman(opens new window) has joined Multiverse as Chief Product Officer.
A native New Yorker with a career built at the intersection of culture and technology, Jay’s fingerprint is on some of the most foundational tech products of the last two decades. From the early days of Hulu(opens new window) to a decade-long tenure helping scale Spotify(opens new window) from a startup to a global powerhouse, and most recently leading AI-driven commerce systems at Amazon(opens new window), Jay has a proven track record of finding the next before it becomes the now.
Now, he’s moved to London to lead the next phase of the Multiverse product journey. We sat down with him on his first day to talk about his bet on the future of AI, the cultural discipline of dogfooding, and the lessons in timing he’s carried from Spotify and Amazon to Multiverse.
As you start this new chapter at Multiverse, what’s one cultural ritual you’re excited to establish to ensure we keep building at the highest possible standard?
Dogfooding.
We should never subject customers to an experience we would not subject ourselves to. If we are lifelong learners, we should be taking the courses we offer and using the products we build as real customers do.
If something frustrates us, confuses us, or feels harder than it should be, we fix it. And we fix it quickly.
We are only as good as the product we put into the world. There is no such thing as a great team building a bad product. And there are no great products that emerge by accident from teams that are not deeply invested in the experience.
To be truly customer obsessed, we have to live with our products every day. We should feel embarrassed when they fall short and genuinely proud when they delight.
That discipline is how high standards become a habit.
Every great CPO leaves a fingerprint on the team they lead. When you look back two years from now, what would you like Multiverse to be known for in the tech community?
I’d like Multiverse to be known as the company that took a different bet.
While much of the tech industry is focused on humans making machines smarter, Multiverse focused on building machines that make humans smarter.
I’d want us to be known for proving that AI can strengthen judgment, accelerate learning, and expand human capability in real work, not just automate tasks or generate outputs. For building systems that people trust because they genuinely make them better at what they do.
If the tech community looks at Multiverse and sees a company that chose depth over hype, capability over convenience, and long-term human impact over short-term efficiency, that’s a fingerprint worth leaving.
That reputation would matter more to me than any single product or feature.
Describe your career in your own words.
I’d describe my career as a long arc of building at the edge of what’s next, and learning a lot about timing along the way.
I’ve always been drawn to inflection points. Moments when technology shifts behavior, but the path forward isn’t obvious yet. I tend to spot those trends early and lean into them, even when the outcomes aren’t guaranteed.
Sometimes that meant being too early. Early in my career, I worked on one of the very first consumer mobile apps built for the Palm Pilot pre-smartphone era. The idea was right, but the world wasn’t ready. The devices needed cellular connectivity, a real app ecosystem, and infrastructure that simply didn’t exist yet. That experience taught me an important lesson: innovation isn’t just about seeing the future, it’s about understanding what needs to be true for it to arrive.
Other times, it meant being early but patient. I was part of the launch of Hulu(opens new window), one of the first major video streaming platforms. While the direction was obvious, mainstream adoption took years to develop. Consumer behavior had to catch up and the industry needed time to recalibrate.
At Spotify(opens new window), the timing was different. The world was ready after Napster. People clearly wanted on-demand access to music. But the business model didn’t exist yet. That challenge required innovation across product, monetization, creator economics, and licensing. It wasn’t just about building a great experience, it was about inventing a system that could sustain it.
More recently at Amazon(opens new window), I’ve been working exclusively on AI products since the moment ChatGPT launched in November 2022. What immediately stood out to me was not just the capability of the technology, but the speed at which it would reshape work itself. That recognition has driven my focus ever since: not just on what AI can do, but on how it changes skills, roles, and expectations.
Looking back, the common thread is a deep curiosity about where things are going, a willingness to act early, and a growing appreciation for timing, execution, and systems that can turn breakthrough ideas into lasting impact.
What’s your fun fact!
The first time I ever went skiing was in college, and I did it in the least sensible way possible.
I had never skied before. I’d never taken a lesson. I joined the ski club anyway, bought second-hand boots and skis that were far too long, wore jeans, a thin shell jacket, no helmet, and went out on opening night.
It was about -29°C, after dark, and the only trail open on the mountain was a double black diamond.
It took me nearly two hours to get down. Every crash meant my skis and poles were scattered somewhere uphill, so I had to hike back up to collect them before continuing. When I finally made it to the bottom, exhausted and frozen, I got back on the lift and went again.
I’m not sure what that says about me, or how “fun” the fact really is, but it’s one of those stories people tend to remember.
Jay’s arrival marks a new chapter for our Product and Engineering teams, one defined by high standards and a relentless focus on human-centric AI.
If you are a builder who wants to join us on our journey, we’re hiring across our Tech team. Click here to see our live jobs(opens new window).
