Position Overview: We are seeking a highly skilled and motivated LLM Engineer / Python Expert to join our dedicated team. The ideal candidate will play a crucial role in integrating Generative AI tools into our investment research management processes. You will work closely with the investment managers and analysts to automate research capabilities, improve data synthesis, and generate deeper investment insights. This position requires a strong background in Python development, experience with large language models (LLMs), and a passion for enhancing productivity through AI-driven solutions.
Your tasks:
Develop and Integrate LLM Solutions:
1. Design, implement, and optimize large language model (LLM) solutions using AWS Bedrock / AWS SageMaker.
2. Build the agenticFlow and agenticGraph using the Langgraph framework.
3. Create and maintain a library of investment research report prompts and templates in collaboration with prompt experts.
4. Implement AI chat-style interactions to refine initial outputs with further prompting.
5. Work with the architecture team to design a robust and scalable architecture for the research management tool which could integrate multiple data sources (e.g., Snowflake).
6. Contribute to the development environment setup alongside the architecture team.
Collaborate on Architecture Design:
1. Work with the architecture team to design a robust and scalable architecture for the research management tool which could integrate multiple data sources (e.g., Snowflake).
2. Contribute to the development environment setup alongside the architecture team.
Data Integration and Management:
1. Connect the tool to the Dataplatform (for example, Snowflake, Databricks, or Fabric) to interpret tabular data and proprietary frameworks.
2. Integrate internal and external data sources.
Support and Maintenance:
1. Address maintenance and ownership of the MVP (Minimum Viable Product) post-build.
2. Utilize the LangSmith framework to trace and understand LLM performance and implementation.
Your profile:
1. Strong background in Python development.
2. Experience with large language models (LLMs).
3. Familiarity with AWS Bedrock / AWS SageMaker.
4. Knowledge of data integration and management.
5. Excellent problem-solving skills and attention to detail.
6. Strong communication and collaboration skills.
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