Group Product Manager, AI
New
Based in the United StatesFull-TimeManager
Salary not disclosed
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Job Details
- Experience
- 10–12+ years of product management experience, including 3–5+ years in leadership roles
- Required Skills
- Artificial IntelligenceMachine LearningProduct ManagementRisk ManagementStakeholder managementPrompt Engineering
Requirements
- 10–12+ years of product management experience, including 3–5+ years in leadership roles managing complex product portfolios or platforms.
- Proven experience building and scaling AI, machine learning, or infrastructure-level products in production environments.
- Strong technical understanding of LLMs, prompt engineering, evaluation frameworks, and agent-based system architectures.
- Experience working on high-scale, high-stakes systems such as payments, risk platforms, or enterprise-grade AI products.
- Ability to engage deeply with engineers and researchers on system design, architecture trade-offs, and technical constraints.
- Strong track record of translating complex technical systems into clear customer and business value.
- Excellent communication, stakeholder management, and executive-level presentation skills.
- Experience operating in fintech or other regulated environments is highly desirable.
Responsibilities
- Own the end-to-end strategy, vision, and roadmap for AI-driven products across consumer and merchant experiences, ensuring alignment with business goals and customer value creation.
- Lead the design and evolution of agentic AI systems, including planning, tool use, orchestration, and decisioning frameworks.
- Identify and prioritize high-impact opportunities where AI can improve personalization, automation, and financial decision outcomes.
- Drive cross-functional alignment across engineering, risk, compliance, legal, and marketing to ensure responsible and scalable product delivery.
- Define and track product success metrics, ensuring measurable outcomes such as adoption, ROI, engagement, and performance improvements.
- Make clear trade-off decisions across model quality, latency, scalability, and cost to ensure optimal product performance in production environments.
- Establish AI product best practices across the broader product organization, influencing standards and development approaches.
- Present product strategy, roadmap priorities, and performance insights to executive stakeholders.
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