Replika
Computer Software / SaaS
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In 2017, no one knew what AI was supposed to be. We built the world's first consumer AI app. Two million people showed up in two months. Today it's over 40 million, and the thing they keep telling us hasn't changed: it helped. It made their life better, steadier, a little less alone.
Most AI is built for tasks, not for people. It gives you answers, but it doesn't care what you do with them. AI doesn't just need intelligence. It needs intention. Because the real question isn't just what AI can do. It's what AI is for.
When the world's leading researchers wanted to understand whether AI could actually change someone's life, they studied Replika, because there was nothing else to study. What they found at Stanford, at Harvard, across years of research, was that Replika doesn't replace human connection. It deepens it. People become more social, more confident, more themselves. Not in theory. In their actual lives.
Every major AI company talks about their mission for humanity. None of them has ever clearly said what they're trying to do for a single person. We will. We want to help you flourish in real life. Not become a better version of yourself, just more yourself. Strong relationships. Better health. Meaning. Momentum. A life that feels worth living while you're living it.
We're building the kind of AI that follows up. That knows the people in your life and nudges you to reach out when it matters. That sends you a poem, just because. The goal is conversations that lead somewhere real. Maybe it's a text you send to a long lost friend. A hobby you pick up again. A moment you show up for yourself.
Everyone else is building AI that thinks. We're building AI that cares.
We’ve just rebuilt Replika and we’re going through a renaissance, and our goal is exponential growth.
Your job is one number: the predicted revenue from every user who installs the app or hits the web funnel. How you move it is up to you — pricing, packaging, retention, activation, whatever the data points to — but realistically most of the win is in monetization, and that’s where you’ll live. Paywalls, offers, pricing tests, subscription mechanics. You take the same traffic and make it worth more.
This is a hands-on, experiment-driven role, not a strategy seat. You form the hypothesis, ship the test, read it honestly, and either scale it or kill it. You’ll work directly with product, engineering, and the CEO, and your changes hit millions of users within weeks, not quarters.
You’ll sit with our GTM teams — user acquisition, web, brand, and data — because revenue per install is a shared number. They bring the user in; you decide how much that user turns out to be worth. This isn’t a broad product role; we’ve got core product and activation covered. We’re hiring you because monetization is where you’ve spent your career, and it’s where you’re better than we are.
Move predicted revenue per install and per web-funnel visitor. That’s the number you own. Everything else is a means to it.
Run monetization experiments end to end. Paywall placement and design, pricing, packaging, offers, trial mechanics, subscription flows — hypothesize, ship an A/B test, read it straight, and scale the winners.
Start from a playbook. You’ve run enough of these to know what usually works and what usually doesn’t, so you begin from patterns, not from zero.
Reach into activation or retention when the numbers say so. If a change there is the fastest path to more revenue, make the case and ship it, but monetization remains the center of gravity.
Keep a steady cadence of tests live. Size each opportunity before you spec it, prioritize by expected revenue impact, and always have the next tests ready, so the pipeline never goes quiet, even when engineering is the bottleneck.
Write short, clear specs: what triggers it, how it's A/B tested, and the rule for calling it. Engineering should be able to build it without a dozen follow-up questions.
Keep an honest record. Log every experiment, what you expected and what actually happened, and say so early when a call was wrong.
Partner with GTM. Revenue per install is shared with UA and web. You don't run ads or user acquisition, but you work closely with the people who do, and feed monetization signal back into how we acquire and price.
Work directly with product, engineering, and the CEO. You’ll be in the room when ideas form, not waiting for a brief.
A product career spent mostly on monetization. Not a generalist who ran a pricing test once — someone whose main body of work is making consumer products earn more per user.
A real track record moving revenue. You’ve owned monetization metrics — ARPU, LTV, conversion, trial-to-paid — and you can show what you moved and how.
At least one original monetization idea you can point to. Something you came up with from first principles, not lifted from a competitor’s playbook. This is the bar that separates you from 99% of the field.
You run experiments as a matter of habit. You’ve designed and read A/B tests and made ship-or-kill calls off the results, not off opinion.
Strong analytical instincts. You pull and sanity-check your own data, size the audience before you write the spec, and you don't confuse a pretty chart with a real result.
You ship. Idea to spec to live to measured, fast.
You use AI tools in your work already — for research, specs, analysis, and moving faster day to day.
You take a position early and in writing, in your own words. Short, plain and to the point.
Fluent English. You can write a spec that doesn’t need rewriting.
Experience monetizing a B2C subscription app, especially one where the value is hard to explain in a single line.
Deep familiarity with a mobile monetization and experimentation stack — paywall and pricing tooling, Amplitude, attribution/MMP setup, feature flags, server-side testing.
Experience with AI-native products or emotionally engaging consumer apps in the social, communication, relationship, or entertainment space.
You’ve worked web-to-app funnels, not just in-app monetization.
You’ve been an early or sole monetization owner and built the testing process where none existed.
Flexible job schedule and generous vacation policy.
Direct impact on millions of worldwide users within months.
Push the boundaries of applied AI in a consumer setting.
Fully remote, able to work CET hours.
After you apply, unlock the direct contact details of the people who actually make the call. A quick follow-up makes you 5x more likely to land an interview.
Marcus Rivera
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