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Full-Stack AI Engineer building scalable applications, distributed systems, and production-grade platforms. Experienced in Python, FastAPI, Next.js, TypeScript, and PostgreSQL, with strong foundations in system design, testing infrastructure, and cloud-native development. I design and ship high-performance systems end-to-end — from responsive full-stack applications to secure, CI/CD-driven deployments using Docker, Kubernetes, and AWS. My focus is on reliability, scalability, and engineering velocity through automation and strong architectural decisions. During my Software Engineering Co-op at Intuit, I improved engineering efficiency and product quality at scale. I migrated the automation framework from Cypress to Playwright, reducing flaky test failures by 65% and cutting execution time from 45 to 28 minutes, accelerating release cycles by 2 days per sprint. I increased test coverage from 42% to 78%, contributing to a 40% reduction in production defects quarter-over-quarter. I also refactored core services and enhanced no-code/low-code capabilities, enabling 3x faster feature iteration, and built intelligent React UI enhancements that reduced form completion time by 35% and configuration-related support tickets by 50%. Beyond engineering, I’ve mentored hundreds of CS students in data structures, algorithms, operating systems, distributed systems, and software engineering — strengthening both my technical depth and ability to communicate complex systems clearly. I’m driven by building scalable, high-impact systems that improve developer velocity and user experience.
Intuit
• Migrated automation test suite from Cypress to Playwright, reducing flaky test failures by 65% and cutting average test execution time from 45 to 28 minutes, accelerating release cycles by 2 days per sprint • Refactored core services and enhanced no-code/low-code capabilities to enable 3x faster iteration on user experiences, reducing feature deployment time from 2 weeks to 4 days using JavaScript/TypeScript • Expanded test coverage from 42% to 78% using Jest and React Testing Library, contributing to a 40% reduction in production bugs quarter-over-quarter • Built intelligent pre-selection functionality for React UI components, reducing form completion time by 35% and decreasing customer support tickets related to configuration errors by 50%.
Have a project in mind or want to collaborate? I'd love to hear from you.
Get In TouchUnited Health Group
Engineered and supported scalable ETL/ELT pipelines across hybrid cloud environments (AWS, Azure, and on-premise systems) using Amazon S3 as the primary data lake storage layer, ensuring high availability, fault tolerance, and optimized data retrieval performance for large-scale healthcare datasets. Developed distributed data processing workflows using PySpark and Apache Spark, enabling transformation of high-volume structured (claims, patient records) and unstructured data (clinical notes, logs) to support NLP models, predictive analytics, and LLM-driven healthcare insights. Implemented real-time and batch ingestion pipelines leveraging Apache Kafka for streaming data, improving latency for downstream analytics and enabling near real-time reporting capabilities. Contributed to enterprise data integration within Microsoft Fabric (Dataflows Gen2), building reusable transformation layers and managing data movement between systems to ensure consistency, reliability, and governance across reporting platforms. Automated orchestration of complex data workflows using Apache Airflow and serverless triggers, reducing manual intervention and improving pipeline monitoring, failure recovery, and SLA compliance. Designed and optimized Star and Snowflake schema data models to support dimensional reporting, improving query performance and enabling scalable enterprise reporting through Power BI dashboards. Applied data governance and security best practices including role-based access control (RBAC), data validation checks, metadata management, and compliance alignment with healthcare data standards to ensure secure and accurate analytics delivery.
California State University, Long Beach
• Assist 70+ students with R, Python (Matplotlib, Seaborn), Kaggle, and Tableau for applied data visualization. • Collaborate with professor to refine labs and assessments; recommendations adopted to improve course outcomes.
California State University, Long Beach
• Support labs and lead study sessions, driving a 30% overall grade improvement among students. • Develop lab handouts, quizzes, and study guides while assisting with grading to strengthen core CS concepts.
California State University, Long Beach
• Provide 1:1 tutoring for 10+ students weekly covering data structures & algorithms, operating systems, databases & distributed systems, computer networks, software engineering, AI, and machine learning. • Lead exam review sessions for 50+ students.