Senior Product Manager (AI Product Team)

Corelight is entering a new phase where AI scales network telemetry to support modern Security Operations Centers (SOCs)

As the Senior Product Manager for the AI Product Team focusing on Knowledge, Context, and Ecosystem, you will own the data enrichment layer that supports both human analysts and automated AI tools. By integrating context from EDRs, CMDBs, and identity management systems, you will organize raw network telemetry into structured operational insights

Your work will help drive our Agentic Triage features, automating manual investigation paths and enabling security operations teams to respond to threats with greater speed and clarity

Manage the Knowledge Layer Roadmap: Define and execute the product roadmap for our security context engine, ensuring contextual data supports human and automated workflows

Develop AI & Automated Workflows: Build out data-delivery capabilities that support LLM-powered security workflows, enabling automated tools to assist in reliable triage outcomes

Design Alert Prioritization Engines: Create customizable data-prioritization engines with robust defaults, giving enterprise teams granular control over their alert telemetry

Build Ecosystem & Partner Integrations: Lead integration strategies across external security tools to pull context from EDR, CMDB, and IAM infrastructure

Conduct Customer Discovery Loops: Work closely with SOC Managers, CISOs, and security teams to validate policy workflows and ensure the data layer maps to real operational needs

Author Functional Technical Requirements: Write clear Product Requirement Documents (PRDs) and user stories, collaborating with Engineering and UX teams to deliver scalable SaaS solutions

Deliver Operational & Executive Reporting: Design dashboards and tracking frameworks that help SOC leadership evaluate detection accuracy and regulatory compliance- Product Management Track Record: 3+ years of direct experience as a Product Manager or Product Owner, with clear success using data-driven workflows and customer discovery

Preferred Assets: Prior experience as a Product Owner in an Agile/Scrum setup; familiarity with data analytics infrastructure; comfort using OpenAPI specifications to understand backend endpoints

User-Centric Focus: A practical commitment to reducing user friction and designing features that ease the day-to-day work of security analysts

Structured Product Discovery: Ability to perform continuous customer discovery and translate qualitative feedback into data-backed requirements

Policy & Compliance Mapping: Experience translating corporate security guidelines and user permissions into functional software controls

Agile Product Management: Competency managing feature lifecycles, sprint plans, and release cycles in an active Agile/Scrum framework

Network Security Foundations: Familiarity with network visibility metrics, network telemetry collections (like IDS/NSM), and baseline protocols

Enterprise Engagement Exposure: Proven background interacting directly with corporate IT and security leadership (CISOs, SOC managers, compliance teams)

SaaS Tech Familiarity: Hands-on experience working with AI tool setups, data policy controls, or shipping multi-tenant cloud-based SaaS security products

Stakeholder Communication: Strong written and verbal skills to articulate product updates and technical tradeoffs clearly to enterprise customers and CISOs

AI & LLM Workflows: Solid understanding of automated AI assistants, LLM integration patterns, prompting workflows, and technical knowledge representation

Cross-Functional Collaboration: Proven ability to build consensus and drive projects forward across Engineering, UX Design, Marketing, and Sales

Education: Bachelor’s degree in Computer Science, Engineering, Cybersecurity, or a related technical field (or equivalent practical enterprise experience)

Cybersecurity Experience: 5+ years of experience in cybersecurity, with a focus on asset intelligence, data enrichment, or SOC operations engineering

Integration & API Familiarity: Understanding of how data contracts and schemas integrate across security tooling environments (EDR, IAM, CMDB)

SOC Domain Knowledge: Strong understanding of standard Security Operations Center processes, alert triage, threat hunting, and validation workflows