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Delinea is seeking a Product Manager to own the discovery pipeline for its identity security platform—the system that finds every identity, account, and resource across an organization's infrastructure. This role sits at the heart of the platform, responsible for discovering identities across AWS, Azure, GCP, SaaS applications, and on-premises directories, then promoting them into a managed state through intelligent rules.
You will own the discovery roadmap and make registration the single integration point for all discovery sources. A key responsibility is consolidating multiple discovery capabilities (several acquired through M&A) into one unified pipeline without losing coverage customers depend on. This includes planning staged cutover, backfill strategies, and rollback paths. You'll define what must ship before retiring legacy capabilities and ensure coverage is never withdrawn ahead of its replacement.
The role requires close collaboration with engineering teams whose connectors and scanners you'll be absorbing and re-homing. You'll be the single point of contact between those teams and your product organization. You'll also gather requirements from internal product teams consuming discovery output, learn their roadmaps, and design services they can adopt without custom integration.
You'll bring non-human and AI agent identities into the pipeline under the same registration and promotion rules as human identities. Security is paramount: you'll hold the bar on credential handling, least-privilege access, and tenant isolation. Success is measured by coverage and time to first result; you'll push API-first design so other teams can integrate independently.
The ideal candidate has 3–5 years of product management experience, ideally in AI/ML, cybersecurity, identity, or enterprise SaaS. You should be familiar with IAM, PAM, and IGA. Technical acumen is essential: solid understanding of modern AI/ML concepts including large language models, multi-agent systems, context engineering, MCP, and A2A protocols. You can discuss technical tradeoffs with engineers and ensure product requirements reflect best practices in agent-enabled systems. Strong collaboration skills across data scientists, engineers, and UX professionals are required, along with knowledge of compliance, security, and privacy best practices for enterprise software.
