Responsibilities
- Define and guide the long-term technical direction for scalable, secure systems enabling autonomous threat detection, retrieval-augmented investigation, and automated remediation.
- Architect and implement the core AI infrastructure that powers intelligent detection and response workflows.
- Develop and deploy large language models, graph-based reasoning systems, and real-time feature pipelines processing massive volumes of security data.
- Ensure robustness and reliability of AI components, including prompt management, model tuning, adversarial testing, performance thresholds, and failover mechanisms.
- Lead and develop engineering teams by mentoring AI specialists, managing team leads, conducting design reviews, enforcing code standards, and promoting security-conscious development.
- Drive end-to-end delivery of complex software initiatives, balancing speed, quality, technical debt, and system sustainability.
- Establish and enforce standards for monitoring, performance, availability, and security in high-scale production environments handling billions of events.
- Work closely with Product, Detection, and Customer Success teams to shape the roadmap, convert business needs into technical specs, and align engineering efforts with customer impact.
- Advance innovation by exploring and integrating emerging technologies such as retrieval-augmented generation, agent-based tool use, and multi-modal models combining text, logs, and graph data.
Work Arrangement
Hybrid
Team
Structure: Multiple engineering teams reporting to the Director. Manages multiple team leads and a diverse cohort of engineers.
