At an AI data startup focused on power grid intelligence (incubated within a leading innovation lab), my role centers on designing and scaling data platforms that enable reliable, ML-ready data across complex systems. I build high-throughput, event-driven architectures with strong guarantees around data quality, consistency, and governance, including privacy-first processing. I work across backend and infrastructure while partnering closely with ML, Data Science, and Product teams to deliver production-grade systems powering real-world AI applications.

At Amazon, my role focused on building and operating large-scale, real-time data platforms that enabled analytics and operational insights across high-volume transactional systems. I designed distributed, event-driven architectures to process streaming and batch data with strong reliability and performance guarantees. I owned production systems end-to-end, driving improvements in scalability, efficiency, and operational excellence, while contributing to system design practices and mentoring engineers across the team.

At Cisco, my role focused on building and modernizing secure, large-scale data processing systems for payroll and compensation platforms. I worked across the stack, developing backend services, data pipelines, and frontend features to support critical business workflows. I led efforts to migrate legacy ETL systems to modern cloud-based architectures, improving scalability, performance, and cost efficiency. My work emphasized reliability, compliance, and maintainability, enabling more resilient systems for complex, high-impact operations.