In my previous role, I designed a cloud-based application that scaled to support over 1 million users. I utilized microservices architecture to ensure scalability and implemented OAuth 2.0 for secure authentication. Additionally, I integrated monitoring tools like Prometheus and Grafana to track performance and security metrics, ensuring the system remained robust under varying loads.

I start by thoroughly assessing the existing system to identify compatibility and potential risks. I then create a phased integration plan, beginning with a pilot implementation to test functionality. For example, I recently integrated a machine learning module into a legacy system by using APIs and containerization, ensuring minimal disruption while enhancing capabilities.

I prioritize performance by conducting load testing and optimizing code for efficiency. I also implement redundancy and failover mechanisms to ensure reliability. For instance, I used Kubernetes for orchestration and auto-scaling in a recent project, which maintained high availability even during peak traffic, reducing downtime to near zero.

I maintain clear and consistent communication through regular updates and collaborative tools like Jira and Confluence. I ensure stakeholders are involved in key decisions by presenting prototypes and progress reports. For example, I facilitated weekly sprint reviews with stakeholders, which helped align expectations and gather feedback early, ensuring the final product met their needs.

In one project, I resolved a critical latency issue in a distributed system by analyzing the data flow and identifying a bottleneck in the database queries. I optimized the queries and introduced caching with Redis, reducing response times by 70%. This solution significantly improved user experience and system efficiency.