Product Manager - Core Design Experience

Summary

Raspberry AI is building an agentic platform that uses AI to transform how fashion and retail products are created and brought to market. The Product Manager will own the core design and generation experience, improving activation, output quality, trust, evaluation, and end-to-end workflow execution through user research, product discovery, and rapid launches.

Responsibilities

• Own the core design and generation experience — the heart of the product, where a designer goes from an idea to something they'd actually put in front of their director
• Own the core generation and design workflow end to end, obsessing over activation and turning a doubtful creative into a believer in their first session
• Define what "good output" means for our users and build the evaluation habits to know whether the product is actually getting better
• Design for trust so non-technical users know when to lean on the model and variability feels graceful instead of broken
• Hold both sides of the enterprise equation — the everyday creative and the director who signs the contract — when their needs pull apart
• Run tight discovery — user interviews, competitive teardowns, heavy dogfooding, often all in the same week — and turn those insights into shipped launches fast
• Define clear product metrics, use quantitative and qualitative evidence to make decisions, and are comfortable in Amplitude

Skills

• Extremely high ownership. You figure out what needs to happen, unblock yourself, and do it. Bad conditions — thin resources, missing data, a hostile stakeholder — are problems you route around or reverse, not reasons it didn't get done
• You have an eye. You can look at several generated design concepts and articulate why some are off and one is sellable. Product sense, for our users, is aesthetic sense plus workflow empathy — and you have both, or are hungry to sharpen them
• A systems thinker. You see the whole ecosystem a feature touches and instinctively flag the thing everyone assumes someone else owns
• A first-principles thinker. You reason from the job-to-be-done and the nature of the medium, and you're willing to throw out a standard AI-product pattern when it doesn't serve our users
• Fluent in — or a fast learner of — probabilistic systems. You think in distributions and evals, not single specs. We care more about how quickly you get this than how many years you've formally done it
• Resilient and creative under real constraints — which is most of the job at an early-stage startup
• AI-native in how you work. Comfortable using ChatGPT, Claude Code, Claude Cowork, Town, or other AI prototyping and productivity tools to accelerate research, prototyping, and execution
• Data-driven. You define clear product metrics, use quantitative and qualitative evidence to make decisions, and are comfortable in Amplitude
• 3–5 years of product experience, having shipped meaningful products end to end with measurable outcomes
• Bonus: direct experience shipping generative-AI or ML-powered products; background in or genuine curiosity about fashion, design, or creative tools; experience with enterprise/B2B products where the buyer and the everyday user are different people

Qualifications

Must Haves

• Extremely high ownership. You figure out what needs to happen, unblock yourself, and do it. Bad conditions — thin resources, missing data, a hostile stakeholder — are problems you route around or reverse, not reasons it didn't get done
• You have an eye. You can look at several generated design concepts and articulate why some are off and one is sellable. Product sense, for our users, is aesthetic sense plus workflow empathy — and you have both, or are hungry to sharpen them
• A systems thinker. You see the whole ecosystem a feature touches and instinctively flag the thing everyone assumes someone else owns
• A first-principles thinker. You reason from the job-to-be-done and the nature of the medium, and you're willing to throw out a standard AI-product pattern when it doesn't serve our users
• Fluent in — or a fast learner of — probabilistic systems. You think in distributions and evals, not single specs. We care more about how quickly you get this than how many years you've formally done it
• Resilient and creative under real constraints — which is most of the job at an early-stage startup
• AI-native in how you work. Comfortable using ChatGPT, Claude Code, Claude Cowork, Town, or other AI prototyping and productivity tools to accelerate research, prototyping, and execution
• Data-driven. You define clear product metrics, use quantitative and qualitative evidence to make decisions, and are comfortable in Amplitude
• 3–5 years of product experience, having shipped meaningful products end to end with measurable outcomes

Nice to Haves

• Bonus: direct experience shipping generative-AI or ML-powered products; background in or genuine curiosity about fashion, design, or creative tools; experience with enterprise/B2B products where the buyer and the everyday user are different people

Benefits

• Innovative culture: own the core of the product at a company where the core •is• the company, building in one of the most exciting and least-solved corners of applied AI
• Growth paths: opportunities to drive impact well beyond your immediate role as the company scales
• Learning & development: annual discretionary stipend for professional development
• Annual company offsite that brings the whole team together
• Small team, high ownership, extremely short distance from your decisions to their impact
• Equity options
• Comprehensive benefits package including health, dental, and vision insurance