We are looking for a motivated and technically curious AI Engineer to join our Machine Learning and AI team on a 6-month fixed-term contract. This is a hands-on, build-first role where you will work directly with end-users and internal stakeholders to design and deploy LLM-based automation solutions that create real commercial value.
You will be embedded in a small, high-impact team of experienced practitioners who are pushing the boundaries of AI in the energy and commodities sector. From day one, you will experiment with agentic workflows, develop AI-powered skills using leading frontier models, and engage directly with business users to understand their needs and translate them into working solutions.
Key Responsibilities
- Collaborate with end-users across trading, operations, and support functions to identify automation opportunities and craft LLM-based solutions tailored to their workflows
- Design, prototype, and iterate on agentic AI workflows that solve real business problems
- Develop reusable AI Skills leveraging leading-edge models and APIs
- Engage regularly with stakeholders to gather feedback and refine solutions
- Contribute to the team's shared knowledge base and document your work clearly
What You Will Learn
- Commodities & finance: Gain exposure to the inner workings of one of the world's largest energy and commodities trading companies, including oil, gas, metals, and shipping markets
- Practical AI in finance: Understand how AI is applied for automation, decision support, and commercial advantage in a fast-paced trading environment
- Agentic systems: Get hands-on experience building with cutting-edge agentic frameworks and access to frontier model capabilities
Qualifications
- Final year or fresh graduate with a technical degree (Computer Science, Engineering, Mathematics, or related field)
- Python is a must: you should be comfortable reading and writing clean, functional code
- Familiarity with AI and LLMs: you understand how language models work and have experimented with them
- Familiarity with Git and version control workflows
- Basic familiarity with Docker or containerisation concepts
- Interest or familiarity with finance, commodities, energy, oil, gas, metals, or shipping
- Exposure to modern full-stack development practices
- Strong ability to engage with and understand the needs of non-technical end-users
- Clear communicator who asks good questions and is eager to learn
Preferred
- Independent and self-organised, able to manage your own time and priorities without hand-holding
- Prior experience building products or shipping projects (side projects welcome)
- A builder mindset, you default to making things rather than just discussing them
- Proficiency in Excel is a plus
- Experience with prompt engineering, RAG, or agent frameworks is advantageous
- Familiarity with cloud platforms (e.g. AWS, Azure, or GCP)
- Familiarity with machine learning and conventional data science methods
- Some knowledge of, experience with, or interest in quantitative finance and derivative markets
