Confluence AI

Building the next generation of Confluence intelligence by strategically utilizing data, Generative AI and ML/NLP techniques to power agentic capabilities and features that fundamentally change how users interact with their content.

Confluence Big Data Platform

Led cross-org Data Lake integration for Confluence unblocking Atlassian Analytics and downstream ML. Built automated data quality systems (32% → 88% reliability). Drove $1M+ annual savings and 70% reduction in engineering escalations via self-serve tooling.

Confluence Analytics

Architected and led the delivery of a new, high-performance real-time analytics platform for Confluence. This solution ingests billions of daily events and serves over 100M requests/day with a strict <500ms P99 latency. By empowering product teams with real-time data access, the platform directly unlocked strategic new smart user experiences like personalized feeds, related content suggestions, and real-time content activity.

Key contributor to the successful launch of the Salesforce Change Data Capture (CDC) platform. I took ownership of stabilizing the solution by leading the debugging and immediate resolution of critical issues, and was responsible for expanding data change capture coverage across the full range of integrated Salesforce products.

Part of the team in charge of the foundational development of Synopsys' software integrity platform.

I designed and implemented the core data model and a network of reliable and low-latency microservices capable of managing and serving data at enterprise scale, enabling seamless data integration across the entire Synopsys product portfolio.

Led the full-stack redesign and implementation of new features for a mission-critical Credit/Underwriting application. Modernized the system with newer technologies to significantly improve performance, reduce latency, and enhance overall reliability, directly enabling underwriters to more efficiently manage customer insurance contracts.