Charm Security builds the Agentic AI Workforce for fraud, scams, and cybercrime prevention and resolution. Our AI agents combine fraud and security expertise with behavioral psychology and a deep understanding of human vulnerabilities to guide real-time prevention, intervention, and resolution in high-risk moments. Acting as expert teammates to fraud, financial crime, security, and customer-facing teams, Charm helps financial institutions reduce losses and operational costs while improving decision quality, speed, and overall effectiveness. Backed by Team8, we are a fast-growing startup defining a new category at the intersection of cybersecurity, fintech, and AI.About the RoleWe're looking for a hands-on Product Manager to join our product team and work alongside the Product Lead to drive execution across Charm's AI-powered platform. You'll own the technical product lifecycle - turning product direction into detailed specs, managing sprint delivery across both an engineering team and a data science/AI team, and keeping the build machine running smoothly. This role is about being the execution and operational backbone of the product: the person who makes sure great ideas actually ship.You'll work closely with the Product Lead on feature scoping and product shaping, contributing research, data, and drafted specs,while independently owning sprint management, backlog grooming, QA, and day-to-day team unblocking. We are seeking a high-potential Product Manager,ideally with experience in working with AI/ML, data-heavy, workflow products, conversation intelligence or customer care platforms, who is eager to accelerate their career and lead significant product growth.What You Will DoOwn sprint planning and delivery across both engineering and data science teams - running ceremonies, managing the backlog, and unblocking day-to-dayWrite detailed product specs and user stories with well-defined acceptance criteria, translating product direction into buildable workPartner hands-on with engineers and designers - reviewing designs, validating releases, and triaging bugsCollaborate with the data science team on AI model requirements and translate model capabilities into product specsConduct user research and structure design partner feedback to inform product shaping decisionsDefine and maintain product instrumentation and usage metrics to measure feature impact