Ayush Prabhakar

Designed and deployed AWS-based cloud automation solutions to streamline campus IT operations, improve system reliability, and reduce incident response times by 55%, supporting academic, administrative, and student service platforms. Built and managed internal APIs and backend services to enable scalable infrastructure for university systems monitoring, reporting, and integrations across learning management systems (LMS), student information systems (SIS), and enterprise applications. Implemented and governed CI/CD pipelines using Jenkins and Docker, automating build, testing, and deployment workflows across development, staging, and production environments to improve release consistency and system stability. Developed operational dashboards and data pipelines using Python and Power BI to monitor system health, uptime, capacity utilization, and service performance, enhancing infrastructure visibility and executive reporting for ITS leadership. Led infrastructure optimization and service automation initiatives, strengthening monitoring frameworks, standardizing deployment processes, and improving availability of mission-critical educational technologies supporting faculty, staff, and students.

Developed backend REST APIs using Python (Flask) to support transaction processing, data validation, and system integrations. Designed and implemented backend business logic for workflow orchestration, ensuring data consistency and reliable processing across services. Integrated backend services with relational and NoSQL databases, handling CRUD operations, transactions, and schema changes. Optimized database queries and data access patterns to improve API response times and support high-throughput backend operations. Built and maintained CI/CD pipelines using Jenkins and GitHub Actions to automate build, test, and deployment processes. Containerized backend services using Docker to ensure consistent deployments across development, test, and production environments. Implemented logging, monitoring, and alerting using AWS CloudWatch and ELK Stack to improve system observability. Analyzed production incidents, performed root cause analysis, and delivered backend fixes within SLA to improve system stability. Collaborated with frontend, QA, and DevOps teams to integrate backend services and support end-to-end application workflows. Contributed to improving backend reliability by refactoring legacy code, upgrading runtimes, and reducing recurring production issues.