# Ethan Wu > Software Engineer at Amazon Location: San Francisco Bay Area, United States Profile: https://flows.cv/ethanwu Software engineer with 5+ years of experience designing and operating high-throughput distributed systems at Amazon across the Payments and Alexa+ (AGI) organizations. Built global data ingestion platforms, ML pipelines, and production LLM workflows with a focus on scalability, performance, and cost efficiency. ## Work Experience ### Software Engineer II - Artificial General Intelligence (Alexa+) @ Amazon Jan 2025 – Jan 2026 | Sunnyvale, CA Led cross-team design for a document understanding and summarization architecture enabling large language models to reason over page layout and structured elements (tables, sections, headers) across different document types. Built a MapReduce-style summarization pipeline to support documents over 14K+ tokens and designed an offline processing workflow, reducing inference latency by 5× and alleviating real-time throughput constraints. Evaluated and benchmarked multiple LLM models to optimize latency, quality, and cost trade-offs for production deployment. ### Software Engineer II - Payments @ Amazon Jan 2022 – Jan 2025 | Seattle, WA Designed and built a new impression logging service to record advertisement views, landing page hits, and application clicks for Amazon Payment products which receive more than 50K TPS worldwide. Created separate data streams and schemas for each client which reduced the blast radius to a client level and decreased onboarding time for new services from 2 months to 2 weeks. Leveraged AWS Kinesis and Batch to deliver impression data to the Data Engineering team in near real time for processing which solved a long term scaling bottleneck. Discovered and fixed an extraneous impression logging call in the current system costing the company 250K annually. Devised a new dynamic linking architecture plan and collaborated with stakeholders from three partner teams to determine the long term vision for how payment product application links would be configured, stored, and shared in the Payments Org. Remodeled the existing configuration pattern to reduce the amount of fields marketers have to configure by > 80%, resulting in a decrease in time needed to launch new campaigns and the probability of a misconfiguration. Expanded the current data model to support flexible schemas allowing Product teams to configure more complex campaign types that will unblock and expedite the launches of three campaigns expected to generate 130+ million dollars annually. Engineered key components and helped launch a service that optimizes the incentive amount advertised to acquire a customer. Designed and built the data ingestion and incentive assignment tools used by the model training pipeline. Optimized the preprocessing step of the incentive assignments pipeline to decrease the steps runtime from 10 hours to 30 minutes which reduced monthly hardware costs from $10K to $2K. Reduced the cost per acquisition by 20% and increased acquisitions by 15% for 10+ clients through this launch. ### Software Engineer I - Payments @ Amazon Jan 2021 – Jan 2022 | Seattle, WA Served as the Black Friday/Cyber Monday Peak Readiness Lead for a team of 10 and was responsible for scaling runtime services and dependencies, conducting load tests, and performing audits across all facets regarding Payment Ad rendering. Identified and mitigated two scaling issues that would have caused a major impact to the advertisement rendering system. Lead team through a peak event which resulted in no major customer impacting tickets and services handling > 10 billion requests worldwide during Black Friday/Cyber Monday. Built a lightweight and scalable service using AWS Lambda, API Gateway, and DynamoDB to provide data for determining a customer’s eligibility for a particular ad. This service reduced the need to scale the current configuration service by 10x, saving $5K in monthly hardware costs. Spearheaded the adoption of the Smithy IDL on the team, updating our data type modeling and making it available for non-Java languages. ### Software Engineering Intern @ Amazon Jan 2020 – Jan 2020 | Seattle, Washington, United States Headed migration from Spring to React on an internal analytics tool for the Payment Products Machine Learning team. Enhanced functionality and UI of the analytics tool to automate the process of adding new model types. Implemented a new testing framework (JEST) to improve debugging and maintainability. ### Teaching Assistant for Computer Organization @ University of North Carolina at Chapel Hill Jan 2019 – Jan 2020 | Chapel Hill, NC Led recitation section for a class of 60. This included guiding the class through weekly lab assignments and diving deep on topics relating to class projects. Provided feedback for quizzes and labs to help improve and create more accurate metrics for student growth. Hosted office hours 7 hours a week to help with topics including: Computer Architecture, Digital Logic, C, and Assembly language ### Residential Computing Consultant @ University of North Carolina at Chapel Hill Jan 2019 – Jan 2020 | Chapel Hill Provided on-site IT support, education and the technology infrastructure for the UNC-Chapel Hill residential communities. Everyday tasks included working with and troubleshooting computer operating systems (Windows, Mac), malware removal, printer functionality, digital marketing, technical writing, and gaming technology. ### Computer Support Technician @ University of North Carolina at Chapel Hill Jan 2018 – Jan 2019 | Chapel Hill, North Carolina Assisted clients with desk-side support Installed Operating Systems, software, and added them to the campus domain. Wrote documentation and produced training videos. Identified and explored solutions to inefficiencies in day to day work. Inventory, surplusing property, and data security. ### MATLAB Teaching Assistant @ North Carolina State University Jan 2017 – Jan 2018 | Raleigh-Durham, North Carolina Area Lab instructor for Intro to MATLAB course at NC State. In charge of leading weekly lab section and hosting office hours to assist students with projects and homework. Responsible for grading course assignments as well as answering questions on the online forum Piazza. ### Student Ambassador @ North Carolina School of Science and Mathematics Jan 2016 – Jan 2017 | Raleigh-Durham, North Carolina Area Provided information to prospective students and parents interested in attending NCSSM through campus tours and panel discussions. Managed social media outreach for NCSSM Admissions Office. ### Research Intern @ Duke University Jan 2016 – Jan 2017 | Raleigh-Durham, North Carolina Area Created simulations with Comsol software to optimize the elimination of tumor cells in the liver using radio frequency ablation. Designed and manufactured sensors for the detection of frequency emissions from Transient Luminous Events in the atmosphere. ## Education ### Bachelor of Science - BS in Computer Science and Statistics The University of North Carolina at Chapel Hill Jan 2018 – Jan 2020 ### Bachelor's degree in Mechanical Engineering North Carolina State University Jan 2017 – Jan 2018 ### High School in Electrical and Electronics Engineering North Carolina School of Science and Mathematics Jan 2015 – Jan 2017 ### High School in Mechanical Engineering North Carolina School of Science and Mathematics Jan 2013 – Jan 2015 ## Contact & Social - LinkedIn: https://linkedin.com/in/ethanhwu - Website: https://www.ethanhaowu.com --- Source: https://flows.cv/ethanwu JSON Resume: https://flows.cv/ethanwu/resume.json Last updated: 2026-03-22