# David Yan > Engineering @ Persona Location: San Francisco Bay Area, United States Profile: https://flows.cv/davidyan2 Experienced backend engineer and AI enthusiast with over 6 years of experience solving complex technical challenges at scale. Expertise spans from building robust, scalable backend systems to designing cutting-edge AI-powered solutions. Passionate about leveraging advanced technologies like Retrieval-Augmented Generation (RAG) and Large Language Models (LLMs) to drive business value and enhance user experiences. Spearheaded the development of a sophisticated AI-driven incident response system, incorporating agentic workflows and context-aware interjections to revolutionize problem-solving processes and significantly reduce Mean Time to Resolution (MTTR) for critical issues. Proven track record in modernizing legacy systems, implementing microservices architectures, and developing high-performance data pipelines that process diverse, unstructured data sources in a flexible, privacy-focused, and fault-tolerant way. Committed to building clean, maintainable code that bridges the gap between resilient backend engineering and emerging artificial intelligence applications, delivering impactful solutions that scale to millions of users. ## Work Experience ### Software Engineer @ Persona Jan 2025 – Present ### Senior Software Engineer, AI Platform Engineering @ Transposit Jan 2023 – Jan 2024 | Palo Alto, California, United States • 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. ### Staff Software Engineer @ Evernote Jan 2022 – Jan 2023 | Redwood City, California, United 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. ### Senior Software Engineer @ Evernote Jan 2020 – Jan 2022 | Redwood City, California 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. ### Software Engineer @ Evernote Jan 2018 – Jan 2020 | Redwood City, California, United States 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. ### Student Researcher @ Duke University Jan 2017 – Jan 2018 | Raleigh-Durham, North Carolina Area - I am currently developing a parallel all pairs shortest path algorithm that primarily targets graphs with many strongly connected components. This work is done with Professor Xiaobai Sun at Duke University. - Created and openly distributed a MPI/C++ benchmarking routine for MPI COMM WORLD communication latency with MATLAB visualization to measure data transmission latency between all machines within a specified computer cluster. ### Student @ Duke University Jan 2014 – Jan 2018 ### Developer @ Duke University Jan 2016 – Jan 2016 - Worked on the Duke University Mobile Medicine Project - Developed an iOS app to collect over 50 million minute by minute movement data points from Fitbit users. - Designed and implemented a data pipeline utilizing the iOS application, Firebase API, and Python automated scripting to fetch, process, and export user movement and heart rate data for time series analysis in Matlab. - Created prediction model for user mood levels based on locomotor movement and sleep data. ### Undergraduate Teaching Assistant, Computer Science 101 Course @ Duke University Jan 2015 – Jan 2015 – Lead and teach a weekly lab programming section to roughly 30 students – Hold weekly consulting hours where I assist students with issues in their code – Assist professors in grading programming assignments and exams ### Software Engineering Intern @ Evernote Jan 2017 – Jan 2017 | San Francisco Bay Area - Full Stack Software Engineering Intern on the Evernote Commerce / Growth Infrastructure team - Designed and implemented a full-stack experiment framework and API that will enable engineers throughout the company to create, view, and gather statistical data on experiments in real time. The framework I developed will encompass Evernote’s 20+ million daily active users. Written primarily in Java and Stripes Framework. ### Software Engineering Intern @ Trading Technologies Jan 2016 – Jan 2016 – Developed Javascript based features to enable high speed web trading on the TT Web trading platform. Optimized data communication pipeline to reduce latency on trading and placing orders by approximately 30%. – Created Slack integration service using Amazon Web Services SDK for NodeJS to instantly display live company analytics within a Slack channel. This feature is in daily use by over 300 members of the company. ## Education ### Bachelor of Science (B.S.) in Computer Science Duke University ### Master of Business Administration - MBA in Business Administration and Management, General University of Washington ## Contact & Social - LinkedIn: https://linkedin.com/in/david-w-yan - Portfolio: http://www.davidwyan.com/ --- Source: https://flows.cv/davidyan2 JSON Resume: https://flows.cv/davidyan2/resume.json Last updated: 2026-04-11