Need a Finetuned LLM model and langchain/llamaindex RAG architecture for industry grade chat with PDF application using GPT-4 API -- 3

I am looking for a skilled developer who can help me with my project. Here are the details:

I am looking for a skilled developer to create a finetuned/ pretrained LLM and design and implement a langchain/llamaindex RAG architecture and incorporate GPT index, Langsmith, and GPT cache for an industry-grade chat application. The application should integrate a PDF feature and have capabilities for source context and indexing (tree index or document summary index).

Design and Functional Requirements:

Specific design and functional requirements are in place for the chat application.
The developer should employ the retriever trained with generative pseudo labeling for domain adaptation (haystack) and be adept at deploying on Azure, offering streaming output.
Knowledge base integration is vital, and suggestions for improvement are always welcome.
Timeline:

Desired Level of Accuracy:
- High accuracy is crucial for the LLM model.

Specific Industries or Domains:
- The chat application will be used in the legal tech industry.

Desired Response Time:
- The chat application should provide responses within a few seconds.

Ideal Skills and Experience:
- Experience in developing and fine-tuning LLM models
- Knowledge of langchain/LLAMaindex RAG architecture
- Proficiency in integrating GPT-4 API
- Familiarity with the legal tech industry

If you have the required skills and experience, please reach out to discuss further details.