Founded in 2019 and part of Y Combinator’s Summer 2020 cohort, Photoroom is the leading AI photo and video solution for e-commerce, helping businesses sell at first sight.
Backed by Series B funding, we’ve reached 300M+ downloads and now process around 7 billion images a year for businesses of every size, from solo sellers to global brands and marketplaces like Amazon, Decathlon, and Depop. We serve them through our mobile app, web platform, and API, with tailored solutions for enterprise catalogs.
We’re an international team of 130+, with offices in Paris and New York. We take ownership of what we build, move quickly to learn what works, and speak candidly, united by our ambition to create exceptional impact for e-commerce businesses worldwide.
We're looking for a Staff Product Manager to own the AI platform every Photoroom product is built on. Our mission is that any team ships best-in-class GenAI visuals without needing a backend engineer: the primitives, the gateway and the no-code tooling turn adding an AI capability into a configuration step rather than an engineering project. On top of that sits the agentic layer — multi-step visual workflows that generate, check, reason, route and publish on their own. Working closely with engineers, ML researchers, and the product teams who ship on your platform, you'll decide what gets built, why, and how it ships.
Location: Paris, (Hybrid)
- Own the platform every AI feature runs through. Expand and improve our AI gateway, including safeguards, evals, cost and observability, giving teams the ability to ship with little to no code and build skills that we can ship directly to users.
- Build the agentic layer and Photoroom’s MCP. Visual agents that run multi-step flows: generate, QA, route, retry, publish, all unattended and at catalog scale.
- Define the problem before the solution. Sharpen the problem, then partner with engineering and research to ship work that feels effortless — for the developers and PMs using the platform as much as for end users.
- Treat other teams as your customers. Every team's roadmap contains AI features gated on platform work. You'll prioritise across them, hold a strategy rather than a request queue, and say no with reasons.
- Turn AI capabilities into products people want. Work hand-in-hand with our researchers and engineers to convert new model capabilities into shipped features that move usage and revenue, and turn them into primitives other teams can reuse.
- Use data to decide, not to justify. Pull and interpret data yourself, such as adoption, latency, inference cost per successful generation, eval results. Form hypotheses, measure what shipped, and call what's next. You won't need to wait around for someone else to run the query.
