# William Wu > Software Engineer | Bachelor's in Computer Science Location: Boston, Massachusetts, United States Profile: https://flows.cv/williamwu Full-stack Software Engineer with 3+ years of professional experience building and deploying scalable, cloud-native applications using React, Node.js, TypeScript, and Spring Boot. Experienced in designing microservices architectures and implementing secure, high-performance systems on AWS and Azure. Proficient in containerization with Docker and orchestration with Kubernetes, enabling resilient, auto-scalable infrastructure. Skilled in RESTful API development, CI/CD automation, and distributed state management with Redux. Passionate about clean code, system reliability, and full-stack performance optimization. ## Work Experience ### Software Engineer @ Precision Insight Solutions Jan 2024 – Present | Dr Allen, TX ● Led architecture and delivery of a high-concurrency live commerce platform, enabling a seamless shopping experience that scaled to 100K+ concurrent purchases per session and drove a 3x increase in order volume. ● Standardized version-controlled command execution for safe event replay and reliable recovery across deployments, enabling deterministic state rebuild in rollback scenarios. ● Architected a resilient order execution pipeline using Redis (for inventory preloading and write-through caching) and Amazon SQS (for traffic shaping and eventual consistency), achieving <200ms p99 latency under peak load. ● Designed a fault-tolerant payment layer by integrating Stripe with Spring Boot, handling asynchronous payment lifecycle events (success, refund, failure) with secure webhook validation and idempotent processing. ● Served as primary on-call for order/payment pipelines during peak sales events, driving high-severity triage across teams, implementing automated rollback tooling, and institutionalizing post-mortem best practices to enhance system resiliency org-wide. ● Wrote unit and integration tests for critical order and payment flows using JUnit and Mockito, ensuring 85% test coverage and preventing regressions in high-concurrency scenarios during peak traffic events. ● Replaced RESTful APIs with GraphQL to enable flexible, fine-grained data access for multiple vendors, allowing customized queries and mutations while reducing over-fetching and simplifying integration workflows. ### Software Engineer @ DeFiner Labs Jan 2023 – Jan 2024 | California, United States ● Led the design of a modular blockchain ingestion system for data teams to collect data from ETH, BSC, and Polygon, with per-chain Spring Boot microservices consuming on-chain data via WebSocket and JSON-RPC polling for fallback and reorg recovery. ● Built a CRON-based multi-level data aggregator with daily to yearly rollups. Applied Memcached for caching, write-behind for daily writes, and double-delete strategy for long-term consistency, improving cache hit rate to over 85% and reducing RDS query load by 40%. ● Developed a resilient observability stack using AWS CloudWatch and DataDog to monitor node health, block lag, ingestion throughput, and P99 API latency. Introduced alert-based auto-recovery workflows, reducing mean time to resolution (MTTR) by over 65%. ● Built a high-throughput transaction search API in Java with JPA and partitioned PostgreSQL, supporting filtering by chain, address, and time. Tuned indexes and queries to reduce latency by 60%.. ● Worked with the data team to gather feedback and improve ingestion and debugging tools, adding 10+ usability features and reducing issue resolution time by 40% across ETH, BSC, and Polygon pipelines. ### Software Engineer @ Joblogic-X Jan 2022 – Jan 2023 | Boston, Massachusetts, United States ● Architected and implemented the backend infrastructure for a short-video platform using Node.js and MongoDB, integrating Azure services (Blob Storage, AD B2C, CDN, Media Services) for identity, storage, and content delivery. Designed for scale and low-latency access under high concurrency. ● Migrated video ingestion from AWS to Azure Media Services for native transcoding and preview generation. Used dual Azure Blob Storage containers (staging + permanent) with SAS access and cleanup policies, reducing review time by 90%. ● Led CI/CD modernization with GitHub Actions and Azure DevOps Pipelines. Integrated feature flagging (Unleash) for controlled rollouts, blue-green deployments, and environment-based toggling across staging and production. ● Developed and maintained automated regression tests for video upload, preview generation, and CDN playback flows. Collaborated with QA to diagnose production issues and improve end-to-end reliability. ● Developed React components for the short-video platform’s upload, playback, and user interaction flows, integrating with Azure Media Services and Blob Storage APIs, improving UI responsiveness and reducing user-reported upload issues by 60%. ● Wrote unit tests for backend services using Jest and Sinon, validating video upload, transcoding, and access logic, which improved test coverage and prevented regressions during CI/CD rollouts. ### Chinese Academy of Sciences @ Chinese Academy of Sciences Jan 2018 – Jan 2019 | Beijing, China • Collaborated with professor on advanced computer vision research, implementing neural network models to analyze and interpret complex visual data, contributing to improvements in image recognition accuracy and performance. ## Education ### Master of Engineering - MEng Northeastern University ### Bachelor's degree in Computer Science Hong Kong Baptist University ## Contact & Social - LinkedIn: https://linkedin.com/in/william-wu-2004b9254 --- Source: https://flows.cv/williamwu JSON Resume: https://flows.cv/williamwu/resume.json Last updated: 2026-03-28