AI Engineer

About Us

Open Mineral is building cutting-edge digital and AI-driven solutions for the base metals commodity trading business. Our Quantitative Research Platform supports signal generation, alpha research, and advanced trading models across global metals markets. We are expanding our AI team to develop the next generation of intelligent trading and research systems.
 

Role Overview

We are seeking an AI Engineer to join our Quantitative Research platform team. The ideal candidate will have strong experience in Python, AWS, and modern AI/ML techniques with a focus on agentic AI systems and prompt engineering. You will work closely with quants, researchers, and traders to build scalable AI-powered infrastructure for trading signals, risk analysis, and decision-making automation.
 

Key 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.
   

Required Skills & Experience

• 3–5 years of experience in AI/ML engineering or applied data science.
• 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.
   

Preferred Qualifications

• Background in quantitative finance or exposure to commodity trading.
• Experience with reinforcement learning, optimization, or simulation frameworks.
• Knowledge of data engineering workflows (ETL pipelines, data lakes, APIs).
• Previous work in high-frequency or systematic trading environments.
   

What We Offer

• Opportunity to build a cutting-edge AI research and trading platform in commodities.
• Work alongside top-tier quant researchers, data scientists, and engineers.
• Competitive compensation package including performance-based bonus.
• Hybrid/remote flexibility with a global, multicultural team.
• Exposure to real-world trading strategies and decision-making in commodity markets.