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LLM Application Full-Stack Developer

China Asset Management Co.,Ltd.
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LLM Application Full-Stack Developer 

Job Overview Join our AI Engineering team to build next-generation LLM-powered applications that transform investment research and client advisory services. You'll develop end-to-end solutions integrating cutting-edge language models with production financial systems, directly impacting trillions in assets under management.

Key Responsibilities

  • Design and implement full-stack LLM applications using modern frameworks (React, Next.js, FastAPI, Node.js)
  • Build and optimize RAG systems integrating proprietary financial data with vector databases (Qdrant, Chroma, FAISS) 
  • Develop LLM workflows using frameworks like LangGraph for document analysis, sentiment analysis, and investment research automation
  • Collaborate with portfolio managers and research analysts to translate business requirements into technical solutions
  • Implement model monitoring, A/B testing, and performance optimization for production LLM systems
  • Build APIs and microservices integrating with Bloomberg, Refinitiv, and alternative data providers 

Required Qualifications

  • Bachelor's degree in Computer Science, Engineering, or related quantitative field
  • Experience in full-stack development with Python, JavaScript/TypeScript
  • Strong experience with LLM frameworks: Hugging Face Transformers, OpenAI API 
  • Proven track record building production ML/AI applications with modern web frameworks
  • Expertise  with containerization (Docker, Kubernetes) 
  • Database proficiency including SQL and vector databases for embedding storage
  • Experience with Git, CI/CD pipelines, and agile development practices

Preferred Qualifications

  • Master's degree in Computer Science, Machine Learning, or related field
  • Financial services experience or strong interest in investment management
  • Experience with fine-tuning LLMs and implementing custom training pipelines
  • Knowledge of financial data APIs (Bloomberg, Alpha Vantage, Quandl) and market data structures 
  • Multi-modal AI experience (image, audio, text, tables, charts, time series)

Technical Skills

  • Programming: Python, JavaScript/TypeScript, SQL, HTML/CSS
  • AI/ML: PyTorch, TensorFlow, scikit-learn, LangChain, Hugging Face 
  • Frontend: React, Next.js, Vue.js, modern CSS frameworks
  • Backend: FastAPI, Node.js, Django, Flask, RESTful APIs
  • DevOps: Docker, Kubernetes, Git, CI/CD, monitoring tools