Product Manager - AI Security Products

About the role

spiderSilk builds a regional, sovereign cybersecurity IP focused on continuous, intelligent and autonomous security. As Product Manager for its AI-driven security products, you will own the vision, strategy and roadmap of the assigned products, partnering with Engineering, Design, Threat Intelligence and Go-to-Market teams to turn complex security challenges into products customers love.

Key responsibilities

• Own the product vision, strategy and roadmap, aligned with company objectives and customer needs
• Partner with Engineering and Design to define, prioritize and deliver features from concept to launch
• Translate customer pain points, market signals and threat landscape insights into requirements and user stories
• Make data-informed prioritization decisions balancing customer value, technical effort and business impact
• Manage the full product lifecycle, from discovery and validation through delivery, iteration and improvement
• Work with Threat Intelligence and Security Research teams so products stay ahead of evolving threats
• Collaborate with Sales, Marketing and Customer Success to drive launches and adoption
• Define, track and report product metrics and KPIs

Required profile

• Proven experience as a Product Manager building technical or B2B software products (cybersecurity, AI, SaaS or infrastructure)
• Strong understanding of the product development lifecycle and agile delivery practices
• Ability to turn complex technical and security concepts into clear requirements and priorities
• Experience managing a product roadmap and prioritizing competing demands in a fast-paced environment
• Excellent communication and stakeholder management across technical and business teams
• Comfort working with data and analytics to inform decisions
• Strong understanding of the technical and security landscape across global markets

Preferred: experience in high-growth or scaling tech environments, familiarity with cybersecurity domains such as threat detection and vulnerability research, exposure to AI/ML-driven products, multi-region engineering collaboration, and a background in technology, engineering or computer science.