Python LLM Engineer

About Caxton Associates:

Caxton Associates, founded in 1983, is a global trading and investment firm with offices in London, New York, Singapore, Monaco, Dubai and Bengaluru. Caxton Associates’ primary business is to manage client and proprietary capital through a suite of products designed to fit the specific needs of investors. Employing a multi-portfolio manager framework, Caxton excels in discretionary global macro investing, leveraging its diversified expertise across asset classes and markets.

About the role:

We are seeking a Python LLM Engineer to join the Software Development team. The Software Development team is responsible for building out the next generation of highly scalable, reusable and performant distributed services and applications for Caxton users.

• Design and deploy LLM-powered Python workflows that integrate into existing business processes.
• Implement retrieval-augmented generation (RAG) and related architectures to ground LLM outputs in Caxton’s proprietary data.
• Architect secure data integrations, linking models to internal knowledge bases, APIs, and document repositories.
• Automate manual research and operational workflows, delivering measurable efficiency and quality improvements.
• Build and maintain robust data pipelines for document parsing, enrichment, and structured data extraction.
• Develop maintainable, testable Python code to support scalable AI services in production.
• Run pilots and proofs of concept, demonstrating value and best practices for AI adoption across the organization.
• Troubleshoot and optimize model performance, retrieval accuracy, and infrastructure reliability.
• Stay current on advances in LLMs, prompt engineering, and applied machine learning; evaluate and prototype emerging methods.

Experience:

• Bachelor’s degree in Computer Science, Mathematics, Engineering, or a related technical field.
• Experience in Python development.
• Experience deploying and supporting Python applications and workflows.
• Familiarity with multi-modal data integration and distributed inference architectures.
• Strong problem-solving and communication skills.
• Some knowledge of cloud services – e.g. AWS/Azure would be beneficial.
• Displays and operates at the highest degree of ethics and integrity.