Passionate about building AI Agent applications using Java, Go, and Python. Focused on bringing LLM capabilities into real-world business scenarios. Experienced in Agent framework development, tool calling, multi-agent collaboration, and other application-layer technologies. Currently seeking opportunities in AI Agent application development.

• Agent Frameworks: AgentScope Java, Spring AI, LangChain4j
• Core Capabilities: ReAct Reasoning, Tool Calling, Memory Management, Multi-Agent Collaboration
• LLM Integration: OpenAI API, DashScope (Qwen), Model Context Protocol (MCP)
• Agent Patterns: ReAct, Function Calling, RAG, Agent Orchestration

• Primary: Java (JDK 17+), Go, Python
• Frameworks: Spring Boot, Spring AI, Project Reactor (Reactive), Gin (Go), FastAPI (Python)
• Architecture: Microservices, RESTful APIs, Event-Driven, Concurrent Programming
• Tools: Maven, Gradle, Docker, Git, Kubernetes

• JVM Internals: Class loading, Bytecode, Memory model, Garbage collection algorithms
• JVM Optimization: GC tuning (G1, ZGC, Shenandoah), Memory profiling, Performance analysis
• Java Concurrency: Thread pools, Lock mechanisms, Concurrent collections, Reactive streams
• Java Low-Level: JNI, Unsafe API, Direct memory, NIO/AIO, Reflection optimization

• Tool System: Annotation-based tool registration, Schema generation
• Memory: Short-term & Long-term memory, External backends (Mem0)
• State Management: Session persistence, Recovery mechanisms
• Integration: Web APIs, Streaming (SSE), Hook system

• 🔍 Open to AI Agent Application Development opportunities - Looking for roles in:
  • AI Agent Application Developer - Building LLM-powered agent applications
  • Agent Framework Developer - Developing Agent frameworks and toolchains
  • LLM Application Engineer - Integrating large language models into business systems
  • Multi-Agent System Developer - Designing and implementing multi-agent collaboration systems

💡 Focus: Agent application development, not model training. Dedicated to building production-ready agent applications using existing LLM capabilities.

Note: The statistics above are fetched from GitHub API and display real activity data for account JGoP-L. If charts appear empty, it may be because the account doesn't have public repositories or contribution records yet.

• Agent Architecture Patterns - ReAct, Plan-and-Execute, Multi-Agent Orchestration
• Production Agent Systems - Scalability, Reliability, Monitoring for Agent applications
• Tool Integration - Building robust tool ecosystems for agents
• Agent Frameworks - Exploring new frameworks and best practices in Java ecosystem

• 📧 Email: [email protected]

Focused on building production-ready AI Agent applications using Java, Go, and Python. I believe that through proper architecture design and engineering practices, AI Agents can be successfully deployed in real business scenarios to solve actual problems. Looking forward to working with like-minded teams to advance Agent application development! 🚀

⭐️ From JGoP-L