• Architected and implemented an advanced Retrieval-Augmented Generation (RAG) system to accelerate incident response, reducing Mean Time to Resolution by 15%.

• Integrated cutting-edge AI technologies, including multimodal embeddings, to enable context-aware interjections and agentic reasoning workflows.

• Enhanced "Human-in-the-loop" processes by providing intelligent assistance for troubleshooting, proactive documentation retrieval, dynamic summarization, and contextual insights to accelerate root-cause analysis.

• Engineered a high-performance, fault-tolerant ingestion pipeline for processing diverse unstructured data sources.

• Developed configurable chunking and multi-format embedding strategies to optimize LLM search flexibility.

• Implemented advanced retrieval mechanisms, such as semantic similarity (top-K), Maximum Marginal Relevance (MMR), and LLM-aided retrieval enhanced with function-calling capabilities.

• Designed a sophisticated customization system with pre- and post-filtering options to allow for experimentation and increased precision.

• Ensured extensibility for seamless integration of new sources, embedding models, and retrieval techniques.

• Incorporated robust security measures such as organization-level data isolation, on-demand data purging, and PII redaction to ensure data privacy and compliance.

• Designed and implemented a worker and job scheduling framework to ensure high availability and reliability for regular data ingestion and indexing workloads. This framework improved system resilience, enabling continuous data ingestion from diverse sources of unstructured data.

• Developed an abstraction layer to manage perpetual, real-time data indexing and periodic reingestion tasks, with automatic error recovery.

• Implemented features such as distributed locking, idempotent job execution, and checkpoint management to handle concurrent workers, ensure data integrity, and support seamless recovery from failure states.

Platform Infrastructure Team

• Led a re-architecture effort of Evernote’s complex backend application while maintaining low latency and high performance requirements to support over 50 million MAU. This reduced hosting costs by 20% while enabling scaling capabilities to support Evernote's product growth.

• Automated and standardized a previously manual weekly release process for backend engineering teams. This alleviated a large developer pain-point, saving an average of 1 hour of dev time per week, enforcing consistency, and ensuring no critical information was missing from release changelogs.

• Led and onboarded a backend team of 8 engineers distributed across North America, South America, Europe, and Asia. Implemented a PagerDuty backend rotation and escalation policy which granted 24/7 active coverage of the core Web Service.

• Facilitated weekly engineering improvement sessions aimed at improving team workflows. Successfully instituted a "2x coverage" rule, ensuring no member held singular expertise on a particular topic. This initiative boosted team cohesion, increased consistency in meeting sprint targets, and reinforced mutual accountability.

Commerce and Growth Infrastructure Team

Evernote Tiers Repackaging

• Led the Commerce Team’s technical implementation of repackaging: updating Evernote’s offerings from 3 tiered Basic/Plus/Premium to 4 tiered Free/Personal/Professional/Teams. Business impact: increased subscription conversion ASP by 15%.

• Coordinated cross-team efforts to ensure consistency in the backend data model changes. Added gating to new features and UI/UX pages to ensure rigorous internal testing.

Commerce Migration Service

• Designed and developed a migration service which was used to systematically transfer over 2 million active Evernote subscribers’ service and subscription data from the legacy commerce service platform to the new microservice-oriented platform. Safely migrated $100M in annual bookings data to the more reliable platform.

Commerce Growth Team

• Implemented and deployed a brand new end-to-end Commerce Service to decouple a 10+ year old monolithic codebase with millions of lines of code into a brand new microservice architecture. This new architecture encompasses all of Evernote’s commerce services including credit card payments, discount offerings, and subscription renewals for millions of annual subscribers.

• Enabled the Commerce Team to move from a fixed weekly release to an on-demand CI/CD release pipeline. Release and build processes that previously took 1 hour were brought down to 15 minutes.