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Obsidian Security is looking for a Senior Staff Platform Product Manager to lead the strategy and execution of core platform capabilities that power multiple products. You’ll work closely with engineering and the PM team to design, scope and deliver shared services, data foundations, and integration patterns that help product teams ship faster and unlock cross-product value.

This role is technical and hands-on: you’ll drive the platform roadmap, define APIs and contracts, evaluate build vs. buy, and ensure platform components are reliable, scalable, and secure. You’ll also lead OEM and partner integrations that extend the platform.

Examples of what you’ll work with Engineering to build and own

1) Identity Graph (Human + Non-Human Identities)

• Partner with Engineering to shape the identity model and core services (human + non-human identities, apps, auth artifacts, entitlements, relationships).
• Turn product needs into platform requirements that power access understanding, SaaS exposure insights, and risk assessment.
• Work closely with PMs to identify dependencies and manage overlapping delivery timelines
• Prioritize and validate capabilities like identity resolution/enrichment, relationship mapping, and change tracking for broad product adoption.

2) Workflow Automation (OEM + Integration)

• Partner with Engineering to evaluate and select an OEM workflow automation engine for remediation.
• Define requirements for one-click and policy-driven auto-remediation, and drive adoption/rollout.
• Collaborate with Engineering to ensure a secure, reusable integration and run a structured evaluation.

3) Sensitive Data Context via Integrations (DSPM/DLP)

• Define platform approach for integrating with DSPM and/or DLP tools.
• Ingest and normalize signals such as: where sensitive data resides, who has access, and who actually accessed it.
• Partner with product stakeholders to ensure integrations deliver actionable context for risk scoring and remediation.

4) Aggregated Customer Intelligence Platform

• Partner with Engineering/Architecture to establish a secure approach for aggregating and analyzing customer signals to generate intelligence that improves our products.
• Define the product requirements and use cases, plus the governance expectations and success metrics.
• Work with Engineering to make the outputs usable by product teams through consistent schemas, APIs, reusable datasets, and clear onboarding/documentation.

5) Applying AI to make the platform differentiated

• Identify high-impact places to apply AI across identity, risk, workflows, and intelligence focused on real customer outcomes.
• Partner with Eng/Data/ML to define AI features like identity inference, smarter risk prioritization, workflow creation/recommendations, and insights from aggregated signals.
• Define data needs, success metrics, and guardrails (security, privacy, auditability, reliability) to ship AI responsibly.

Responsibilities

• Own the platform roadmap for shared components used by multiple product lines; drive alignment across engineering and product stakeholders.
• Translate complex customer and business problems into platform requirements, services, and APIs.
• Partner deeply with engineering on architecture, tradeoffs, sequencing, and technical debt management.
• Lead OEM/vendor selection and integration execution.

Required qualifications

• 5+ years experience in Product Management, with significant work on platform, security, or data products.
• Strong technical fluency: able to work effectively with engineering on APIs, data models, access control systems, reporting, event systems, integration patterns, and distributed systems tradeoffs.
• Experience shipping shared platform components used by multiple teams/products.
• Confidence and familiarity with the  cybersecurity space.

Preferred qualifications

• Experience with identity and access concepts: IAM, OAuth/OIDC, SCIM, RBAC/ABAC, service principals/non-human identities, audit logs.
• Familiarity with workflow automation concepts.
• Exposure to DSPM/DLP ecosystems and/or sensitive data governance patterns.
• Strong written communication and ability to influence across a multi-product organization.