Jan 2024 – Present · 2 yrs 5 mos · India

• Migrated a decade-old TurboGears-based monolith from bare-metal deployment to a containerized architecture, integrating with GitHub Actions for automated image builds, CI/CD, and one-click deployments.
• Architected extensions to support multiple Synopsys products with distinct release models, workflows, and check-in criteria, enabling unified tooling, configuration flexibility, and collaboration across diverse engineering teams.
• Built a custom VS Code extension integrated with GitHub Copilot as part of a Retrieval-Augmented Generation (RAG) system, enabling multi-agent chat and FAQ resolution for internal Synopsys tools.
• Implemented a BM25-based document retrieval engine, optimized for CPU-only environments to eliminate GPU dependency and reduce resource usage.
• Designed an intelligent log monitoring and alerting framework leveraging transformer embeddings, cosine similarity, and Microsoft Teams integration, providing near real-time error detection and notification.
• Developed automated data extraction pipelines and scripts in Python (pandas) to collect and preprocess metrics across systems; shared reusable modules to streamline analysis workflows across teams.
• Architected and deployed an analytics layer using Streamlit, Pandas, and Plotly, integrating data from multiple systems to visualize usage statistics, approval TAT, and process bottlenecks, enabling data-driven decision-making and continuous workflow optimization.

Mar 2022 – Dec 2023 · 1 yr 9 mos · India

• Spearheaded the redesign and implementation of the core streaming methodology for Synopsys'
• developer tools' real-time ETL data pipeline, achieving a notable enhancement of 99% in data availability and integrity.
• Designed and Implemented data transformations using KSQL and Kafka Streams to achieve optimal datasets consumed by the business.
• Containerized Kafka clusters and Elasticsearch nodes using Docker, resulting in a 50% reduction in deployment time and improved infrastructure portability and scalability.
• Developed a customized monitoring and self-healing system for Kafka clusters using Python, providing real-time insights into cluster performance.
• Collaborated with cross-functional teams to implement load balancing for ELK and Kafka clusters, utilizing F5 LTM hardware,enhancing traffic distribution and overall performance.
• Played a key role in enhancing the user experience of Python-based Synopsys developer tools (TurboGears framework) throughnumerous bug fixes and feature enhancements, resulting in a more streamlined and user-friendly interface.
• Applied Python-based data analysis for multiple product teams, delivering valuable insights to support decision-making processes.
• Utilized Agile methodologies to drive continuous improvement, taking ownership of problems end-to-end and contributing to the enhancement of data sources and business rules.