Drive customer adoption of BrazeAI by leading workshops, diagnostics, and accelerators from AI use-case ideation through launch and impact measurement. Advise technical and marketing stakeholders, identify adoption barriers, develop AI playbooks and prototypes, recommend services partners, and provide AI thought leadership. The role combines customer-facing consulting, marketing technology expertise, applied AI knowledge, and cross-functional collaboration, with travel up to 25% at peak times.

Own and evolve Braze’s ML platform for production-scale training, deployment, serving, observability, reliability, and cost efficiency. Lead complex infrastructure initiatives, including multi-region model serving, customer-specific model pipelines, CI/CD tooling, orchestration, and cloud identity. Set technical direction, manage incidents, collaborate across teams, improve engineering quality, mentor senior engineers and data scientists, and connect platform decisions to business outcomes.

Lead the technical vision and delivery of production machine learning systems, including distributed training, model serving, lifecycle management, and customer-specific model pipelines. Drive cross-team initiatives, establish engineering best practices, improve ML platform reliability and scalability, mentor senior engineers and data scientists, and connect technical decisions to customer and business outcomes.