Own a core area of the XDR roadmap end to end: drive detection, correlation, incident building, and response capabilities across endpoint, cloud, identity, and network, from requirements through shipped and iterated product.

Expand and maintain the telemetry and integrations XDR depends on: first-party Elastic data plus third-party EDR, cloud, identity, and network sources that let the product correlate across a real environment.

Contribute to Elastic's exposure and vulnerability management work, including prioritization based on exploitability and reachability rather than raw CVSS, and remediation workflow.

Write requirements engineering can act on without follow-up clarification meetings, and translate customer input and threat research from Elastic Security Labs into product.

Represent product in customer conversations, including senior security stakeholders, and bring what you learn back into the roadmap.

Ensure your capabilities work across Elastic's deployment models, from cloud to on-premises to air-gapped, so they hold up in regulated and disconnected environments.

Maintain well-developed awareness of the competitive landscape and GTM strategies.

Create artifacts such as roadmap trackers and decision memos that give stakeholders visibility without requiring a meeting.

Experience: At least 5 years in security-related technical product management, competitive analysis, or technical marketing, and a minimum of 3 years in a related product development or technical field. A track record of owning product areas from requirements through shipped, iterated outcomes.

Detection and Response Domain Knowledge: Hands-on knowledge of XDR, EDR, SIEM, incident response, or forensic either as a product manager or as a practitioner such as a SOC analyst, detection engineer, or incident responder. You can discuss correlation, response, and detection engineering credibly. A practitioner background before transitioning into product is a solid plus.

Telemetry and Integration Breadth: Comfort building or owning products that rely on heterogeneous third-party data, with a awareness that XDR depends on ingestion breadth and healthy integrations.

Analytics and Threat Understanding: A solid comprehension of the analytics techniques behind detection and prioritization and of the current cyber threat landscape. Familiarity with AI security, how AI, ML, and agentic systems are attacked and defended, is a plus. Solid comprehension is required; hands-on modeling is not.

Technical Credibility: You earn respect from engineering through the quality of your requirements, and you know enough about architecture to judge feasibility and scope.

Customer-Facing Confidence: You are comfortable representing product to security customers, including senior stakeholders, and can hold both the practitioner and the leadership view in the same conversation.

Communication Excellence: You can distill complex detection engineering and exposure concepts into clear narratives for both technical and non-technical audiences.

Comfortable with AI-Augmented Work: You use AI tooling for synthesis, research, and delivery as a regular part of your workflow, and you own the final outcomes regardless of how they were produced.

Cross-functional Collaboration: You have operated across Product, Engineering, Sales, and Customer Success, and you drive execution in a dynamic, remote-first environment with growing autonomy.

Proficiency and Education: A robust interest in cybersecurity and its challenges is essential. Attention to detail is important. You must also have the ability to understand the bigger picture. A BS or MS degree in engineering, computer science, or information security is required.

Own a core area of the XDR roadmap end to end: drive detection, correlation, incident building, and response capabilities across endpoint, cloud, identity, and network, from requirements through shipped and iterated product.

Expand and maintain the telemetry and integrations XDR depends on: first-party Elastic data plus third-party EDR, cloud, identity, and network sources that let the product correlate across a real environment.

Contribute to Elastic's exposure and vulnerability management work, including prioritization based on exploitability and reachability rather than raw CVSS, and remediation workflow.

Write requirements engineering can act on without follow-up clarification meetings, and translate customer input and threat research from Elastic Security Labs into product.

Represent product in customer conversations, including senior security stakeholders, and bring what you learn back into the roadmap.

Ensure your capabilities work across Elastic's deployment models, from cloud to on-premises to air-gapped, so they hold up in regulated and disconnected environments.

Maintain well-developed awareness of the competitive landscape and GTM strategies.

Create artifacts such as roadmap trackers and decision memos that give stakeholders visibility without requiring a meeting.

Experience: At least 5 years in security-related technical product management, competitive analysis, or technical marketing, and a minimum of 3 years in a related product development or technical field. A track record of owning product areas from requirements through shipped, iterated outcomes.

Detection and Response Domain Knowledge: Hands-on knowledge of XDR, EDR, SIEM, incident response, or forensic either as a product manager or as a practitioner such as a SOC analyst, detection engineer, or incident responder. You can discuss correlation, response, and detection engineering credibly. A practitioner background before transitioning into product is a solid plus.

Telemetry and Integration Breadth: Comfort building or owning products that rely on heterogeneous third-party data, with a awareness that XDR depends on ingestion breadth and healthy integrations.

Analytics and Threat Understanding: A solid comprehension of the analytics techniques behind detection and prioritization and of the current cyber threat landscape. Familiarity with AI security, how AI, ML, and agentic systems are attacked and defended, is a plus. Solid comprehension is required; hands-on modeling is not.

Technical Credibility: You earn respect from engineering through the quality of your requirements, and you know enough about architecture to judge feasibility and scope.

Customer-Facing Confidence: You are comfortable representing product to security customers, including senior stakeholders, and can hold both the practitioner and the leadership view in the same conversation.

Communication Excellence: You can distill complex detection engineering and exposure concepts into clear narratives for both technical and non-technical audiences.

Comfortable with AI-Augmented Work: You use AI tooling for synthesis, research, and delivery as a regular part of your workflow, and you own the final outcomes regardless of how they were produced.

Cross-functional Collaboration: You have operated across Product, Engineering, Sales, and Customer Success, and you drive execution in a dynamic, remote-first environment with growing autonomy.

Proficiency and Education: A robust interest in cybersecurity and its challenges is essential. Attention to detail is important. You must also have the ability to understand the bigger picture. A BS or MS degree in engineering, computer science, or information security is required.