Architects and develops AI-powered systems, backend services, APIs, experimentation frameworks, and automation using foundational models. Integrates AI capabilities with microservices, AWS, Snowflake, and diverse technology stacks while ensuring scalability, reliability, and maintainability. Collaborates with product, data science, and engineering teams to translate business needs into technical solutions, evaluate emerging AI tools, and rapidly prototype proof-of-concept applications.

Lead end-to-end data science initiatives: design, deploy, and monitor ML/statistical models for credit risk, pricing, collections and fraud. Collaborate cross-functionally to integrate models into production, define model development standards, mentor team members, and maintain scalable ML pipelines and monitoring systems to drive measurable business impact.

Design, build, and operate an online feature store and associated batch/streaming pipelines. Optimize Postgres schemas for real-time feature serving, ensure reliability and freshness for ML models, lead technical enhancements, partner with cross-functional teams, mentor junior engineers, and contribute to code reviews and system design.