Yogesh R

Key Achievements

• Built and maintained a comprehensive connector ecosystem enabling dataset imports from most relational and NoSQL databases, major Microsoft 365 and Google Workspace apps, cloud file stores (e.g., Amazon S3, Azure Blob/Containers, GCS), and messaging platforms (Slack, Microsoft Teams).
• Implemented permission-aware AI deployments that inherit and enforce connector-level permissions, ensuring secure, least-privilege data access in production.
• Created connector tools for AI Agents to securely fetch data at runtime on behalf of users, with auditability and fine-grained scopes.
• Developed a generic OAuth connector framework to onboard any OAuth-based service for data ingestion with minimal engineering effort, supporting token refresh, multi-tenant consent, and incremental scopes.
• Added incremental sync for large datasets across connectors, dramatically reducing transfer volume and improving end-to-end latency.
• Optimized legacy connector code paths for high-throughput ingestion, reducing sync times and improving reliability at scale.
• Led development of a Jenkins observability dashboard (React, Next.js, Python, MySQL) that identified costly tests and inefficiencies—actions from the insights reduced compute costs by $7,500 per month.

Technologies Used

Key Achievements

• Led design and development of full-stack testing portal used by 500+ QA engineers
• Built backend in Python with asynchronous log parsing (asyncio), delivering 25% performance improvement over legacy Perl system
• Developed responsive UI using React and Next.js with PostgreSQL data storage
• Achieved 60% reduction in report generation and rendering time
• Containerized application with Docker and deployed with Nginx
• Integrated GitLab CI/CD pipelines for automated testing and deployment
• Built Python scripts for regex-based log parsing and test debugging
• Contributed to bug fixes and performance enhancements in internal tools (Python and Go)

Technologies Used