JAVA BACKEND ENGINEER · HANGZHOU
Java backend engineer with 4+ years on core business systems. I focus on monetization money-flow, payment integration, real-time risk control and complex system migration, with an eye on reliability, scalability and engineering efficiency.
JOURNEY / EXPERIENCE
@ Mogujie
Owned product, merchant, marketing-campaign, monetization money-flow and payment capabilities — including merchant onboarding review, lucky-draw payouts, membership days, Google Pay and hybrid payment integration. Took over and stabilized a real-time risk-control system, building rate limiting, circuit breaking, graceful degradation and fault isolation, and supported complex cross-team system delivery.
@ Tencent
Independently built an internal security platform in Python and helped fix security issues in cloud products. Contributed to the CI/CD pipeline, delivering with Docker, bastion hosts and enterprise Git conventions.
@ Xi'an Xurui Vision Intelligent Technology
Worked on admin management, smart-camera control and video-conferencing systems, handling Nginx push/pull streaming and working with audio/video protocols such as WebRTC and RTMP and their business architecture.
SELECTED WORK / PROJECTS
Owned the core rebate pipeline across twelve e-commerce and local-life channels, unifying promotion link conversion, user attribution, order feedback reconciliation, commission calculation, fund payout and reverse claw-back. Through channel-strategy onboarding, fund idempotency, distributed scheduling and daily settlement reconciliation, long-cycle asynchronous orders became traceable and compensable, with low-cost onboarding of new channels.
Read case study↗Led a high-risk migration of the core product pipeline, keeping compatibility across multiple categories, SKUs, virtual goods, membership goods and external product mappings. Designed model mapping, old/new product identifiers, dual-write reconciliation and canary cutover, migrating 15,000+ products and related data with zero major incidents and zero business interruption.
Read case study↗Turned the company's internal real-time risk-control capability into an independently deliverable engineering product. Decoupled the rule engine, feature platform and decision modules from data and messaging dependencies, and provided an SDK, deployment/migration, canary rollback, load testing and standardized onboarding docs.
Read case study↗An open-source campus community WeChat Mini Program built from scratch, with modules for a confession wall, lost & found, second-hand trading, forums and carpooling. It went through a full launch, operation and archival lifecycle.
Read case study↗A self-built cross-platform (macOS / Windows) desktop watcher for ETFs and ETF options, combining dual-source real-time quotes, multi-timeframe K-lines, volume-price patterns, intraday momentum, an option T-quote board and strategy analysis, with native notifications and local data storage. It evolved from the earlier Ying+ multi-client investment app and was narrowed into a local alerting tool to respect market-data licensing and compliance boundaries.
Read case study↗ABOUT
BSc in Software Engineering, based in Hangzhou, China. I have long owned the design and maintenance of core internet business systems spanning products, merchants, marketing campaigns, monetization money-flow, payment integration and real-time risk control.
I work well in high-concurrency, fast-changing and resource-constrained environments, breaking down architecture, driving reliability and delivering across teams. I have run a zero-downtime migration of 15,000+ products, delivered a real-time risk-control system to external environments, and owned the core calculation module of a multi-platform rebate system.
Outside work I keep maintaining open-source projects and a quantitative-trading system, and I explore engineering AI into content generation, decision support and internal tooling. I believe in simple, direct code and long-term, steadily evolving systems.
AI LAB / EXPERIMENTS
A same-item retrieval system for fashion, built for content placement. I owned the vector index layer, the Kafka CDC ingestion pipeline, price filtering and AI cost governance. Built on FastAPI, Elasticsearch nested dense_vector and multimodal models, it serves image-to-item, text-to-item and content-style matching over 120k+ products and 210k+ SKU vectors.
The AI content engineering practice inside the Ying+ multi-client investment app: market, sector, holdings and watchlist data are turned into a structured Context, and DeepSeek generates an AI morning brief, daily review and position advice, with data-readiness checks, idempotent generation, back-office review and a permission/billing flow. Productization has stopped; it is kept as a record of AI application engineering and financial-data systems.
CONTACT