We're looking for a seasoned Senior Technical Product Manager — GenAI & Agentic Systems to drive the development of AI solutions across Machine Learning and Generative AI, turning advanced models into scalable products that improve operational efficiency, compliance, and customer experiences.

🎯 Responsibilities

• Partner with senior product leadership and cross-functional product managers to align your domain roadmap with the broader AI strategy.
• Own complex, high-stakes AI workstreams with a high degree of autonomy.
• Drive measurable business impact across areas such as back-office operations, real-time fraud and AML detection, and personalized B2C growth and marketing journeys.
• Lead the end-to-end delivery of Machine Learning and GenAI initiatives, from initial hypothesis, data scoping, and evaluation framework design through production deployment and post-launch monitoring.
• Act as a technical partner to Data Scientists and ML Engineers, translating business constraints into model requirements and ensuring architectures address real consumer and operational needs.
• Balance rapid innovation with the security, auditability, data privacy, and reliability standards required in a regulated banking environment.
• Define standards, blueprints, and self-service toolkits that enable product squads to adopt AI capabilities safely and independently.

🛠️ Requirements

• 5+ years of Product Management experience in a technology-driven environment.
• Proven experience owning and launching production-grade AI/ML capabilities.
• Hands-on experience taking GenAI products from concept to production, including customer-facing or platform products powered by AI.
• Practical experience with Retrieval-Augmented Generation (RAG), agentic workflows such as the ReAct framework, state and memory management, function calling, and multi-agent orchestration systems.
• Experience in high-volume, highly scalable technical domains such as B2C FinTech, e-commerce, or high-traffic consumer technology. Experience limited to low-scale B2B environments does not meet the requirements of this role.
• Comprehensive knowledge of the AI/ML product lifecycle, including problem scoping, target metric definition, data ingestion and labeling, model training and fine-tuning, evaluation framework design, deployment, latency optimization, and continuous retraining.
• Strong foundation in traditional Machine Learning methodologies, including classification, regression, and ranking or recommendation engines.
• Hands-on expertise with modern LLM architectures.
• Ability to evaluate trade-offs between LLMs and deterministic ML or rule-based logic across cost, inference latency, explainability, and accuracy.
• Ability to define, track, and translate offline model evaluation metrics—including precision, recall, F1, confidence thresholds, and hallucination rates—into business KPIs and operational ROI.
• Strong collaboration skills in Agile environments.
• Understanding of financial services requirements, including GDPR, data residency, the EU AI Act, risk governance, and security controls.

🌟 Working style

• Take pragmatic, high-velocity action and focus on creating value, balancing model perfection with incremental delivery.
• Maintain high standards for system resilience and production reliability.
• Communicate comfortably with Principal Data Scientists and Platform Engineers while explaining complex model behavior clearly to non-technical leaders.

🤗 Benefits

• Competitive personal development budget.
• Work-from-home budget.
• Discounts on fitness and wellness memberships, language apps, and public transportation.
• Premium subscription for your personal bank account, plus subscriptions for friends and family members.
• One additional day of annual leave for each year of service.
• High degree of autonomy and access to cutting-edge technologies.
• Opportunity to work with colleagues from diverse nationalities, life experiences, and backgrounds.
• Relocation package with visa support for eligible candidates.