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  • Beijing, China

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hkun0120/README.md

Hong Kun | AI × Data Systems × Web3 Engineer

Beijing, China | Remote OK
Email: phnasis@126.com


👋 About Me

I am an AI & Data Systems Engineer with 14+ years of experience building large-scale, high-availability data platforms in financial and regulated environments.

My work focuses on turning complex systems into intelligent, reliable, and scalable products — especially at the intersection of:

  • AI Agents & RAG pipelines
  • Real-time data infrastructure
  • Workflow orchestration & optimization
  • Web3-native data & oracle systems

I enjoy working on problems where data, system design, and intelligence meet real production constraints.


🧠 Core Expertise

AI & Intelligence Systems

  • AI-assisted scheduling & decision systems
  • Log intelligence & failure explanation using LLMs
  • RAG pipelines for structured + unstructured data
  • Feature engineering on DAGs, execution traces, and system metrics
  • Reinforcement-learning–inspired optimization (DDQN / IDDQN)

Data & Backend Engineering

  • High-throughput ETL & streaming pipelines
  • Kafka / RabbitMQ
  • PostgreSQL / MySQL / Oracle
  • Elasticsearch (large-scale indexing & search)
  • Low-latency, high-availability system design

System Architecture

  • Workflow orchestration (DolphinScheduler)
  • Multi-cluster & multi-tenant architectures
  • Observability, performance profiling, fault diagnosis
  • Financial-grade stability & reliability engineering

Tech Stack

Java · Python · Kafka · Redis · Elasticsearch · Docker · Linux


🚀 Selected Projects

🔹 Intelligent Data Scheduling Platform (China Life)

Group-level scheduling platform serving regulatory reporting, AML, actuarial, risk control, and data platform teams.

What I built

  • Multi-cluster scheduling architecture (commercial + open-source clusters)
  • AI-assisted scheduling to replace rule-based execution
  • Execution log intelligence for failure analysis and root-cause explanation
  • DAG semantic modeling (dependencies, resources, duration)

Impact

  • 40–50% reduction in critical workflow MAKESPAN
  • Significant improvement in cluster resource utilization
  • 1000+ internal users, million-level task executions
  • Zero major production incidents

📄 More details


🔹 National Core Data Query Platform

Unified data access layer for 36 provinces, serving over 1M internal users.

Highlights

  • 10M daily queries

  • 99.92% requests completed under 1s
  • Zero major incidents since launch
  • Cross-team architecture leadership (60+ engineers)

📄 More details


🌐 Web3 & AI Interests

I am particularly interested in:

  • Agentic Oracles & Social Signal Processing
  • Prediction Markets & Market Intelligence
  • On-chain / Off-chain data pipelines
  • Solana ecosystem infrastructure

📄 Notes & explorations


📫 Contact

If you're building at the intersection of AI, data infrastructure, and Web3,
I’d love to chat.

📧 phnasis@126.com
🌍 Open to remote & early-stage teams

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