Deploy onsite with strategic customers to understand security and risk workflows, build AI-native solutions, analyze data, and integrate SecurityScorecard with enterprise systems. Design cloud architectures across AWS, Azure, and GCP; prototype and productionize software; translate security data into financial risk insights; and maintain technical relationships through renewals and expansion. Travel to customer sites for workshops, technical discovery, and go-live support.

Develop, evaluate, and deploy machine learning models for risk scoring, threat intelligence, and vendor risk assessment. Perform exploratory data analysis on large datasets, validate models for accuracy and scalability, and integrate models into production with engineering and product teams. Communicate findings to technical and non-technical stakeholders and stay current on research and methods.

Lead design, build, and scale of secure, multi-tenant Kubernetes infrastructure and CI/CD systems. Own AI tooling infrastructure and MCP servers, implement GitOps and IaC, run streaming analytics (Kafka, Flink, ClickHouse), improve observability and SLOs, lead incident response and postmortems, and mentor engineering teams on reliability, automation, and progressive delivery strategies.