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Product Manager – AI Security
Pragmatike. Own the roadmap, requirements, and prioritization for the product area from discovery through launch .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in Product Management for B2B SaaS, with a strong focus on AI security and cloud infrastructure. Capable of translating customer needs into actionable product strategies while leveraging AI tools and workflows for effective product development.
Highest-signal resume keywords
Product Management ExperienceAI Security KnowledgeCloud Infrastructure ExpertiseTechnical Fluency in APIsExperience with AI Compliance Frameworks
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Product Roadmap DevelopmentCustomer DiscoveryTechnical Design ReviewsSuccess Metrics DefinitionAPI Specification ReadingPython ScriptingAI Tools UtilizationLLM Application DeploymentPRD CreationCybersecurity Knowledge
Soft Skills
Strong Written CommunicationIndependent OperationCollaboration Across Time ZonesOwnership
Tools & Technologies
AI ToolsCloud ServicesIAMDLPCASBSIEMEDRCSPM/CNAPP
Industry Keywords
B2B SaaSAI SecurityCybersecurityRegulatory FrameworksDistributed Systems
Tech Stack
Tools & technologiesCloudCyber SecurityPython
About the role
Key responsibilities & impact- Own the roadmap, requirements, and prioritization for the product area from discovery through launch
- Lead customer discovery with CISOs, security architects, and cloud/AI platform teams
- Translate customer needs into clear problem statements and PRDs
- Partner with engineering and security research on scope, technical trade-offs, and delivery
- Participate in technical design reviews
- Define success metrics and measure adoption, coverage, and detection effectiveness
- Work with product marketing, sales engineering, and support on positioning, enablement, and launches
- Track the evolving AI security landscape, including agent frameworks, LLM providers, regulation, and competitors
- Translate relevant AI security developments into product strategy
- Use AI tools and agentic workflows for research, analysis, documentation, and daily product work
- Own either the Cloud Discovery workstream, building an inventory of AI agents, models, and AI-enabled applications across customer cloud environments, or the AI Security Platform workstream across gateway, agentic security, forensics, or shared platform capabilities
Requirements
What you’ll need- 5+ years of Product Management experience in B2B SaaS
- 2+ years working on security, cloud infrastructure, or developer-facing products
- Proven track record of shipping products used by enterprise security or infrastructure teams, with measurable outcomes
- Strong technical fluency, including reading API specifications, discussing distributed-systems trade-offs, and understanding deployment of LLM applications and AI agents
- Strong written communication and ability to produce clear PRDs, decision documents, and executive updates
- Practical, daily use of AI tools and LLM/agentic workflows in product work
- Fluent English
- Comfortable collaborating with distributed teams across time zones
- Strong ownership and ability to operate independently in a fast-moving environment
- Experience in cybersecurity, including DLP, CASB, SIEM, EDR, CSPM/CNAPP, or AI security
- Strong practical knowledge of a major cloud provider, including services, IAM, and inventory/audit APIs
- Engineering background or hands-on scripting experience, particularly Python
- Experience with AI compliance and regulatory frameworks such as the EU AI Act or NIST AI RMF
- Experience introducing AI-assisted or agentic workflows into product teams
Benefits
Comp & perks- Fair, transparent, and inclusive recruitment process
- AI tools and agentic workflows integrated into daily work
- Opportunity to shape a new product line at the intersection of cybersecurity and agentic AI
- Direct collaboration with engineering, security research, and enterprise customers
- Significant product ownership with high visibility and influence
- Opportunity to help define enterprise AI security practices
- Highly technical, distributed team