Collaborate with GTM leadership and account teams to design and execute high-impact engagement strategies across your territory, driving Lakewatch adoption from initial data offload through full SIEM augmentation or replacement.

As a trusted advisor, serve as an expert Solutions Architect building technical credibility with CISOs, security architects, SOC leadership, and security analysts to drive product adoption and vision.

Enable clients at scale through workshops, POC execution, and developing customer-facing collateral that increases technical knowledge and demonstrates the value of an open agentic SIEM architecture.

Influence product roadmap by translating field-derived, data-driven insights into strategic recommendations for Product and Engineering teams.

Handle the most complex technical challenges in this product line by acting as the tier-3 escalation point for the field, ensuring customer success in mission-critical security environments.

Establish and refine the sales qualification and POC intake process, ensuring well-scoped engagements that maximize customer success and minimize friction for R&D.

The ideal candidate will have 5+ years of experience in a customer-facing, pre-sales or consulting role influencing technical executives, driving high-level security strategy and product adoption.

Experience with design and implementation of data and AI applications in cybersecurity, including anomaly detection, behavioral analytics, and agentic AI workflows for triage and investigation.

Proficient in programming, debugging, and problem-solving using SQL and Python and with AI tools.

Experience collaborating with Global System Integrators (GSIs) and third-party consulting organizations to drive customer outcomes in cybersecurity.

Hands-on experience building solutions within major public cloud environments (AWS, Azure, or GCP), with an understanding of cloud-native security logging and monitoring.

Deep experience in security operations, with broad familiarity across one or more of the following: data engineering, data warehousing, AI/ML for security, data governance, and streaming.

Undergraduate degree (or higher) in a technical field such as Computer Science, Cybersecurity, Applied Mathematics, Engineering or similar.

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