Sr Product Manager - Platform
Listed on 2026-01-24
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IT/Tech
Cybersecurity, Cloud Computing, Systems Engineer, AI Engineer
Founded in 2017, Obsidian Security was created to close a critical gap: securing the SaaS applications where modern business happens—platforms like Microsoft 365, Salesforce, and hundreds more.
Backed by top investors including Greylock, Norwest Venture Partners, and IVP, we’ve built a complete SaaS security platform to reduce risk, detect and respond to threats, and prevent breaches at the source. Our team includes leaders who helped define the categories of endpoint and identity security at Crowd Strike, Okta, Cylance, and Carbon Black.
Now, we’re transforming how SaaS is secured—in the era of agentic AI.
Today, Obsidian is trusted by global enterprises like Snowflake, T‑Mobile, and Pure Storage. We protect more than 200 organizations across North America, Europe, the Middle East, Southeast Asia, Australia, and New Zealand—including many of the world’s largest Fortune 1000 and Global 2000 companies.
With strong global momentum, a growing partner ecosystem including Sentinel One, Databricks, and Google Cloud, and a major fundraise on the horizon, we’re scaling quickly toward long‑term growth and IPO readiness. Join us as we define the future of SaaS security!
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 own1) 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.
- Own the platform roadmap for shared components used by multiple product lines; drive alignment…
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