194K–265K USD / year
Staff Product Manager, Agentic Data Platform
ProductHybrid — San Francisco, California, New York City, New York
Published on 2026-10-27
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About this role
Lead the strategy and roadmap for NodeZero’s data and machine learning platform, turning offensive security data into scalable services for product, ML, and agentic systems. Own platform performance, reliability, governance, adoption, and economics, connecting infrastructure investments to customer and business outcomes.
About the company
Horizon3.ai is a technology company specializing in cybersecurity solutions, focusing on automated penetration testing and threat detection for enterprises. They provide a range of services aimed at enhancing security posture and risk management for organizations across various sectors.
The team
Product and Product Management
Stack
Relational databasesGraph databasesVector databasesMachine learning infrastructureFeature storesMLflowKubeflowAmazon SageMaker
What you'll do
- Set the vision and multi-quarter roadmap for data services and the ML platform.
- Guide managed database services, including provisioning, scaling, migrations, and lifecycle management.
- Own strategy for the unified asset and attack graph, data APIs, pipelines, and integrations.
- Enable production ML workflows, from training datasets and feature stores to deployment and monitoring.
- Define platform reliability, security, governance, and data quality requirements.
- Manage infrastructure investment cases, cost optimization, and platform economics.
- Drive internal platform adoption and connect capabilities to customer value and business growth.
- Define and track platform, operational, financial, and business performance metrics.
What we're looking for
- 8+ years of product management experience, including 4+ years in infrastructure, data, or ML platforms for B2B SaaS.
- Strong understanding of production databases, data platforms, pipelines, APIs, and distributed architectures.
- Knowledge of traditional ML infrastructure, including training pipelines, feature stores, model registries, and production monitoring.
- Experience with data governance and security in multi-tenant SaaS environments.
- Financial acumen in infrastructure cost modeling, ROI, and cloud spending.
- Track record of driving adoption of shared internal platforms and migrations.
- Ability to influence senior technical and executive stakeholders and translate technical trade-offs into business outcomes.
Nice to have
- Background as a database, data, or ML engineer; SRE; or technical founder.
- Experience with security data platforms such as XDR, SIEM, or exposure management.
- Familiarity with graph modeling, entity resolution, vector databases, or semantic search.
- Experience with labeling pipelines, ground-truth datasets, or training data infrastructure.
- FinOps experience or certification.
- Understanding of generative AI data needs, including embeddings, vector search, and fine-tuning datasets.
- Bachelor’s degree in a technical field; an advanced degree is preferred.
Benefits
- Stock options
- Health, vision, and dental insurance for employees and families
- Flexible vacation policy
- Generous parental leave