BZ
Binliu's Doodles

Selected work

Systems built around real problems.

Case studies from food delivery, mobility, and fintech platforms where I led automation, data, and experimentation initiatives.

  1. Help Experience Orchestration Layer

    Event-driven automation powering JET’s help chatbot. The orchestration layer coordinates services, state, and playbooks so order issues resolve without manual intervention.

    Impact

    • Automated resolution flows for millions of annual customer contacts, reducing manual interventions by 60%.
    • Improved stability and MTTR with resilient retries, stateful orchestration, and structured observability.

    What I did

    • Owned architecture, API contracts, and rollout strategy across product, operations, and support teams.
    • Partnered with ops to codify playbooks into reusable workflows, guardrails, and experimentable policies.
    • Java
    • Spring Boot
    • Kafka
    • AWS SQS
    • Redis
    Experience Overview

  2. JETMS Operational Platform

    Multi-tenant workspace that unifies 20+ internal services for customer support agents. CQRS routing, shared data models, and fine-grained permissions keep teams focused on resolution outcomes.

    Impact

    • Reduced issue-resolution SLA by ~33% by consolidating fragmented tooling into a single experience.
    • Enabled market-specific workflows with tenant-aware routing and flexible schema evolution.

    What I did

    • Design service decomposition, and front-end framework-agnostic architecture.
    • Leverage CQRS patterns and governance for integrating partner teams.
    • Java
    • TypeScript
    • Micro Frontends
    • MySQL
    Experience Overview

  3. MapYourCity Crowdsourcing Platform

    Crowdsourced geospatial data engine fueling Grab’s mobility and delivery products. Coordinates contributor tasks, validates submissions, and feeds downstream routing services.

    Impact

    • Scaled to 300K tasks and 400K+ geospatial data points that improved map freshness and trip accuracy.
    • Cut geospatial storage costs by 70% via data simplification and tiered retention policies.

    What I did

    • Designed task lifecycle, task modeling, and auditing capabilities across data, ops, and product teams.
    • Implemented high-performance services in Go, PostGIS, and Kafka with proactive monitoring and alerting.
    • Go
    • PostgreSQL
    • PostGIS
    • Kafka
    • ElasticSearch
    Live DemoExperience Overview

Also built

Other Projects

Additional initiatives that strengthened observability, experimentation, and developer velocity.

  1. 01
    Experiment dashboard mockup

    Darwin Experimentation Platform

    Re-architected experimentation APIs and SDKs at Ant Group to support 1,000+ annual experiments and drive a 2% conversion lift.

    • Java
    • SDK
    • Experimentation
  2. 02
    Street-view map tiles

    KartaView Street-View Service

    High-performance PostGIS service applying the Douglas–Peucker algorithm to shrink geospatial datasets by 70% for faster queries.

    • Go
    • PostGIS
    • Microservices
    Visit project