N26

We're looking for a Senior Product Manager – Conversational Banking to drive the development and deployment of high-impact conversational capabilities and autonomous customer journeys from discovery through delivery and measured resolution outcomes.

🎯 Responsibilities

1. Take full product ownership of complex customer journeys and agent-facing capabilities, translating strategic priorities into clear roadmaps and squad deliverables
2. Lead discovery into contact drivers by developing problem statements from customer feedback, operational data, and contact centre insights
3. Work closely with engineering and applied AI teams to move journeys from answering questions to taking action, delivering safe autonomous resolution with robust guardrails and escalation paths
4. Define and monitor resolution-first metrics, containment rates, and counter-metrics to ensure operational efficiency never compromises quality or customer trust
5. Collaborate with operations, service partners, and peer product teams to integrate AI capabilities into agent workflows and back-office tools
6. Build compliance, auditability, data privacy, and customer protection into every capability from the outset
7. Work alongside Lead Product Managers, Data Scientists, and ML Engineers to deliver conversational experiences used by millions of customers across Europe

🛠️ Requirements

1. 5+ years of product management experience
2. Proven track record of delivering complex digital products or major automation capabilities end to end
3. Hands-on experience with AI-powered, conversational, or LLM-based products in a live production environment
4. Strong ability to analyse datasets, define metric frameworks, and distinguish meaningful signals from vanity metrics
5. Pragmatic, action-oriented approach and comfort working with ambiguity in a fast-moving programme

➕ Nice to have

1. Experience in banking, fintech, or another regulated industry
2. Exposure to contact centre operations, BPO environments, or customer service tooling

🤗 Benefits

1. Competitive personal development budget
2. Work-from-home budget
3. Fitness and wellness discounts
4. Public transportation subsidies
5. Premium bank account subscription for you, plus subscriptions for friends and family
6. One additional day of annual leave for each year of service
7. High autonomy to help shape the ML technical agenda while working with a diverse, international team
8. Relocation package with visa support for those who need it

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

1. Partner with senior product leadership and cross-functional product managers to align your domain roadmap with the broader AI strategy.
2. Own complex, high-stakes AI workstreams with a high degree of autonomy.
3. Drive measurable business impact across areas such as back-office operations, real-time fraud and AML detection, and personalized B2C growth and marketing journeys.
4. 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.
5. 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.
6. Balance rapid innovation with the security, auditability, data privacy, and reliability standards required in a regulated banking environment.
7. Define standards, blueprints, and self-service toolkits that enable product squads to adopt AI capabilities safely and independently.

🛠️ Requirements

1. 5+ years of Product Management experience in a technology-driven environment.
2. Proven experience owning and launching production-grade AI/ML capabilities.
3. Hands-on experience taking GenAI products from concept to production, including customer-facing or platform products powered by AI.
4. 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.
5. 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.
6. 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.
7. Strong foundation in traditional Machine Learning methodologies, including classification, regression, and ranking or recommendation engines.
8. Hands-on expertise with modern LLM architectures.
9. Ability to evaluate trade-offs between LLMs and deterministic ML or rule-based logic across cost, inference latency, explainability, and accuracy.
10. 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.
11. Strong collaboration skills in Agile environments.
12. Understanding of financial services requirements, including GDPR, data residency, the EU AI Act, risk governance, and security controls.

🌟 Working style

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

🤗 Benefits

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

We're looking for a data-driven Technical Product Manager – Applied Machine Learning to build and deploy machine learning solutions that help internal teams scale operations efficiently and securely.

🎯 Responsibilities

1. Execute the machine learning product roadmap in partnership with Senior and Lead Product Managers, owning feature delivery from discovery through deployment.
2. Connect Data Scientists, ML Engineers, and business stakeholders by translating operational challenges into technical specifications, user stories, and acceptance criteria.
3. Deliver predictive models that address internal bottlenecks, automate back-office tasks, accelerate document verification, and improve fraud detection accuracy.
4. Define, monitor, and analyze performance metrics for live models, including production accuracy, latency, and false positive rates.
5. Identify opportunities for continuous model retraining and optimization based on business and model performance data.
6. Partner with engineering leads to refine product backlogs, write detailed user stories, and participate in daily sprint rituals.
7. Maintain a steady, reliable delivery pace while upholding strict security standards.

🛠️ Requirements

1. At least 4 years of experience as a Product Manager in a technology-driven environment.
2. Hands-on experience with, or a strong interest in, data products, analytics, or machine learning workflows.
3. Strong data fluency, including the ability to query and analyze datasets independently using SQL.
4. Experience using data visualization platforms to evaluate model impact and validate hypotheses.
5. Solid understanding of core machine learning concepts, including classification, regression, decision trees, and the model lifecycle from data collection through deployment.
6. Ability to interpret model evaluation metrics, including precision, recall, and F1 score, and connect them to operational outcomes such as saved handling hours or reduced fraud losses.
7. Ability to translate complex business rules into precise technical requirements for engineers.
8. Ability to explain model outputs and limitations clearly to operational teams.
9. Strong focus on delivering pragmatic, incremental value rather than waiting for perfect data.
10. Curiosity about complex backend processes and a structured approach to identifying the root causes of operational challenges.
11. Understanding of the security, compliance, and data privacy requirements involved in delivering software within a regulated financial institution.

🤗 Benefits

1. Personal development budget.
2. Work-from-home budget.
3. Discounts for fitness and wellness memberships.
4. Language app subscriptions.
5. Public transportation benefits.
6. Premium subscription for your personal bank account, plus subscriptions for friends and family members.
7. One additional annual leave day for each year of service.
8. High degree of autonomy and access to cutting-edge technologies.
9. Relocation package with visa support for eligible employees.