Building on Social + Generative AI

I instruct undergrad students in MS Excel, MS Access, Python, and SQL, for data management and analysis.

• Orchestrated the development of a fully automated CI/CD pipeline utilizing GitLab, Terraform, and Azure DevOps, leading to a reduction in deployment time from 4 hours to 2 hours and a 75% increase in deployment frequency, thereby impacting a significant codebase and driving increased efficiency.• Implemented a Kubernetes and Terraform-based cluster management solution for a high-traffic microservices architecture. Leveraged Terraform's infrastructure as code approach to automate deployment workflows, while utilizing Kubernetes' auto-scaling and rolling update capabilities to optimize scalability and minimize downtime.• Deployed 50+ EC2 instances, fine-tuned RDS database configurations, and optimized S3 bucket management, yielding a 40% boost in productivity.• Led a team of 5 junior DevOps engineers, providing guidance on implementing security best practices and conducting regular vulnerability assessments. This initiative resulted in a 25% improvement in team productivity, ensuring system integrity and compliance with industry standards.

• Implemented Python-based automated solutions, reducing manual data aggregation efforts by 50 hours monthly and incorporating performance optimizations for enhanced efficiency.• Enhanced performance for a customer-facing portal serving 10,000+ daily users by transitioning from a monolithic app to a Microservices architecture, implementing memory optimizations to ensure optimal resource utilization.• Developed and executed API unit tests, resulting in a 25% reduction in errors and a 15% enhancement in overall quality, while integrating performance optimizations to maintain robust data integrity and system responsiveness.• Engineered a robust caching mechanism using Redis to optimize data retrieval and improve system responsiveness, resulting in a 40% reduction in average API response times and enhanced user experience.