Senior Product Manager - Platform

About Delinea: Delinea is a pioneer in securing human and machine identities through intelligent, centralized authorization, empowering organizations to seamlessly govern their interactions across the modern enterprise. Leveraging AI-powered intelligence, Delinea’s leading cloud-native Identity Security Platform applies context throughout the entire identity lifecycle – across cloud and traditional infrastructure, data, SaaS applications, and AI. It is the only platform that enables you to discover all identities – including workforce, IT administrator, developers, and machines – assign appropriate access levels, detect irregularities, and respond to threats in real-time. With deployment in weeks, not months, 90% fewer resources to manage than the nearest competitor, and a 99.995% uptime, Delinea delivers robust security and operational efficiency without compromise. 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Join our passionate, global team at Delinea and help us make the world a safer and more secure place. Our success is driven by world-class product leadership, outstanding engineers, and strategic investment from TPG. We value diversity, innovation, and a culture of respect and fairness. If you're ready to push boundaries and challenge the status quo in security, we want to hear from you. Apply today to help us achieve our mission. POSITION SUMMARY Delinea is seeking a Senior Product Manager to define what risk means in our identity security platform and then ship it. The score is the visible half: every account, secret, and permission carries one, with weighting a customer can inspect, a trace showing which signals moved it, and thresholds they set to their own tolerance. The other half is our posture and detection surface, including the checks customers run today, the findings and cases those checks raise, and the reporting required. You will decide what that surface becomes, and you will need agreement across more than one engineering organization to get there. Risk and posture feed the authorization layer that decides who gets access in the moment, so what customers see becomes something we act on. Expect close work with data science, revenue operations, and the field. KEY RESPONSIBILITIES - Define the strategy for identity risk and posture, and say what a score has to mean before a customer will act on it. - Own scoring end to end: the model, the weighting behind it, the trace that shows which signals moved a score, and the controls a customer uses to tune it. - Decide which third-party signals feed the score, including those from providers like Okta and Entra, and what a score is worth for a customer who has connected none of them. - Set direction for the posture and detection surface customers use today: the checks library, the findings and cases it raises, and the reporting that carries them outward. - Deliver posture findings customers can act on, each carrying what was observed, when, and against which resource. - Hold the security and privacy bar for a product built on customer identity data, including tenant isolation, access control on score traces, and watch-before-enforce so a scoring change never locks a customer out. - Work with customers, design partners, and the field to understand the risk they are trying to reduce, and validate requirements before we build. - Learn the roadmaps of the product teams that consume risk signals, and design services they can adopt without a custom integration. - Publish adoption metrics for risk and posture and hold the product to them, and push API-first design so other teams can integrate on their own. - Track where identity security posture management, shared signals, and AI agent identity standards are heading, and feed that into the roadmap. Skills & Requirements - Experience: 5+ years in product management, preferably in AI/ML, cybersecurity, identity, or enterprise SaaS. - Domain Expertise: Familiarity with identity and access management (IAM), privileged access management (PAM), and identity governance (IGA). - Technical Acumen: Solid understanding of modern AI/ML concepts—including large language models, multi-agent systems, context engineering, MCP (Model Context Protocol), A2A (Agent-to-Agent Protocol), and expertise in model fine-tuning and training. Ability to discuss technical tradeoffs with engineering teams and ensure product requirements reflect best practices in agent-enabled systems. - Collaboration Skills: Proven ability to work alongside data scientists, engineers, and UX professionals to define, prioritize, and deliver solutions that balance technical viability, scalability, and u