The company is looking to modernize global trade of base metals through digital and AI-driven platforms that enhance transparency, speed, and efficiency.
Requirements
- Strong proficiency in Python (NumPy, Pandas, PyTorch/TensorFlow, LangChain or similar);
- Familiarity with MCP (Model Context Protocol) or similar orchestration frameworks;
- Experience with AWS (EC2, S3, Lambda, SageMaker, Step Functions, etc.);
- Hands-on expertise in agentic AI frameworks, multi-agent systems, or LLM orchestration;
- Proficiency in Prompt Engineering for LLMs and workflow optimization;
- Understanding of financial markets, quantitative research, or commodities trading (preferably base metals);
- Strong software engineering background, including version control (Git), testing, and CI/CD;
Responsibilities
- Design, build, and maintain AI agents to support trading, risk, and research workflows;
- Implement LLM-driven prompt engineering for data extraction, transformation, and knowledge integration;
- Collaborate with Quant Researchers to translate trading strategies into AI-enabled systems;
- Deploy and scale solutions on AWS cloud infrastructure with best practices in performance and security;
- Develop pipelines for integrating market, fundamental, and alternative datasets into AI/ML workflows;
- Partner with data engineers and software developers to integrate AI models into the Quantitative Research Platform;
- Contribute to the development of multi-agent coordination frameworks to support automated decision-making in commodity trading.
Other
- At least an Intermediate English level (both spoken and written);
- 3–5 years of experience in AI/ML engineering or applied data science;
- People-oriented management without bureaucracy;
- Flexible schedule;
- 25 working days of annual paid vacation;
