Lead the architecture and development of production-grade multi-agent systems and AI-powered security chatbots. Build applied LLM workflows for alert triage, summarization, and automation; create evaluation harnesses; monitor and improve production behavior; establish standards for retrieval, context engineering, tool design, and safety; and embed security controls such as privacy, access controls, and prompt-injection defenses. Collaborate across data science, engineering, product, and platform teams to move AI capabilities from prototype to production.

Build and maintain security automation solutions, reusable components, playbooks, apps, and dashboards for Swimlane Turbine and its Marketplace. Translate SOC and MSSP workflows into configurable enterprise content, normalize security data using Python and JavaScript, integrate SIEM, EDR/XDR, identity, threat intelligence, ticketing, and cloud security tools, and incorporate controlled AI-assisted workflows. Own testing, documentation, versioning, release quality, and cross-functional collaboration.

Build and maintain standardized container images and reliable, observable CI/CD pipelines for a cloud-native platform. Improve build performance, security, reproducibility, dependency management, caching, and supply-chain security. Integrate vulnerability scanning, reduce remediation time, document golden paths, and improve developer experience. The role partners across engineering and security teams, influences platform architecture and tooling, and enables teams to ship safely and efficiently.