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Product Manager, Risk Automation
Rol remoto de 10103 Business - Product - Cash App con fit claro de ubicación del candidato.
PublicadoAgregado recientemente
Países elegibles27 países aceptados
Señal de seniorityLead
Modelo de trabajoRemoto
Ubicaciones aceptadas para candidatos
Resumen del rol
Product Manager, Risk Automation
Requisitos y responsabilidades
Contenido del rol extraído en secciones para revisar más rápido.
You Will
- Own the strategy and roadmap for AI-powered products and capabilities
- Identify AI opportunities grounded in user needs and measurable business value
- Translate ambiguous problem spaces into clear product requirements
- Work closely with ML engineers, data scientists, and researchers on model goals, data needs, evaluation methods, and quality gates
- Build and run experiments to validate hypotheses and iterate quickly
- Define how the product should behave across success, failure, and edge cases
- Establish metrics for accuracy, safety, latency, reliability, and UX satisfaction
- Partner with design on intuitive, transparent, and safe human-AI interactions
- Collaborate with legal, security, and compliance teams to ensure responsible AI practices
- Lead cross-functional execution from concept through launch and iteration
You Have
- 6-9 years of product management experience including a proven track record launching successful AI or ML driven products.
- Strong technical intuition about ML models, training loops, evaluation, prompt design, data pipelines, and real-time inference constraints
- Experience designing and running structured experiments, including A/B tests and offline evaluations
- An ownership mentality with the ability to rapidly drive complex, cross-functional initiatives from strategy through execution at scale.
- Excellent communicator, capable of distilling complex technical concepts into clear narratives for executive, operational, and technical audiences. Ability to work across scaled risk, compliance, and operational teams in a regulated industry.
- Familiarity with AI quality, safety, and responsible-use frameworks
- Experience with LLMs, multimodal models, or applied generative AI
- Experience building operational tooling that drives cost savings and quality
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