Product Manager AI Personalization

Trafilea is a Consumer Tech Platform for Transformative Brand Growth. We’re building the AI Growth Engine that powers the next generation of consumer brands.

With over $1B+ in cumulative revenue, 12M+ customers, and 500+ talents across 19 countries, we combine technology, growth marketing, and operational excellence to scale purpose-driven, digitally native brands.

We own and operate our own digitally native brands (not an agency), with presence in Walmart, Nordstrom, and Amazon, and a strong global D2C footprint.

We’re looking for a Product Manager – AI Personalization to own and evolve our TrafiPersonalization Engine, a hybrid platform combining Machine Learning models, Generative AI, and rules-based logic to deliver real-time, cross-channel personalized experiences across our ecosystem.

This is a high-ownership platform role at the intersection of MarTech, ML infrastructure, and Generative AI applications.

Transform behavioral data and product signals into intelligent, scalable personalization that drives CVR, AOV, and retention across PDP, checkout, email, loyalty flows, and beyond.

You’ll partner with Data Science, AI Engineers, CRM, and Growth PMs to define, ship, and scale personalization use cases — from product recommendations to AI-generated messaging and dynamic experiences.

• Deploy ML and Generative AI use cases (LLMs, embeddings, prompt-based systems).

• Design personalized prompts, smart product bundles, dynamic flows, and AI-driven messaging.

• Define behavioral inputs, decision logic, and fallback strategies.

• Own the vision and roadmap for the TrafiPersonalization Engine.

• Translate business needs into rules logic, APIs, event triggers, and scalable data schemas.

• Ensure real-time personalization across web, CRM, checkout, and lifecycle systems.

• Partner with Growth teams to launch high-ROI personalization initiatives.

• Define experimentation scope and KPI tracking (CVR uplift, RPV, CTR, LTV).

• Enable lifecycle and funnel teams to personalize at scale.

• Act as orchestrator across Engineering, Data Science, CRM, UX, and Analytics.

• Drive rollout plans, QA strategy, documentation, and adoption.

• Evangelize personalization strategy across brands and squads.