The opportunity
We recognize that our strength lies in our people and the varied perspectives they bring to our workforce. We strive to build talented and diverse teams to drive our business success and empower our people to reach their full potential.
What you'll do
Partner Strategically with Senior Product Leadership: Work closely with cross-functional PM leads to shape and align your domain roadmap with N26’s broader company-wide AI strategy, maintaining full autonomy over complex, high-stakes workstreams.
Drive Measurable Business Impact: Focus on high-impact areas, including automating back-office Operations, enhancing real-time fraud and AML detection (FinCrime), and personalizing B2C customer growth and marketing journeys.
Own the Production AI Lifecycle: Lead end to end delivery for complex Machine Learning and GenAI initiatives—moving from initial hypothesis, data scoping, and model evaluation harnesses to production deployment and post-launch monitoring.
Bridge Engineering and Business Strategy: Act as the technical sparring partner for Data Scientists and ML Engineers, translating business constraints into model requirements and ensuring technical architectures solve real consumer and operational problems.
Balance Velocity with Banking Rigor: Manage day-to-day delivery, maintaining a healthy balance between launching innovative AI capabilities and upholding the strict security, auditability, data privacy, and reliability standards expected of a regulated bank.
Empower Autonomous AI Adoption: Act as an AI evangelist and platform owner by defining standards, blueprints, and self-service toolkits that allow product squads across N26 to integrate AI capabilities into their own features safely and independently.
What they're looking for
- + years of Product Management experience in a technology-driven environment,: with a proven track record of owning and shipping production-grade AI/ML capabilities.
- Real-World GenAI & Agentic Systems Production Experience: Hands-on experience taking GenAI products from concept to live production. You must have direct experience building with concepts like Retrieval-Augmented Generation (RAG), Agentic workflows (ReAct framework, state/memory management, function-calling), and multi-agent orchestration systems. (Note: Utilizing off-the-shelf AI productivity tools is not sufficient; we require a track record of building customer-facing or platform products powered by AI).
- B2C Domain Scale (Technical Background Preferred): Experience working within high-volume, highly scalable technical domains (such as B2C FinTech, E-Commerce, or high-traffic consumer tech). Note: Pure B2B background with low customer scale does not fit the high-volume requirements of this role.
- Full AI/ML Specialization: Comprehensive expertise navigating the full AI product lifecycle, including problem scoping, target metric definition, data ingestion/labeling, model training/fine-tuning, evaluation framework design, deployment, latency optimization, and continuous retraining.
