GenAI Engineer

We are looking for a motivated and technically curious AI Engineer to join our AI team. 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 build agentic workflows, develop AI Skills and MCPs using leading frontier models, and engage directly with business users to understand their needs and translate them into working solutions.
This role expects active ownership from day one: you will be accountable for your deliverables and expected to drive delivery and operate with a high level of autonomy.
Key Responsibilities
Collaborate with end-users across trading, operations, and support functions to identify automation opportunities and develop LLM-based solutions tailored to their workflows
Design, prototype, and iterate on agentic AI workflows that solve real business problems
Develop production-ready prompts, AI Skills, and MCPs
Engage regularly with stakeholders to gather feedback and refine solutions
Translate business problems into clear technical requirements, solution designs, and delivery plans to build, integrate, and deploy solutions
Contribute to the team's shared knowledge base and document your work clearly
What You'll Gain
Commodities & finance: Work at the heart of one of the world's largest energy and commodities trading companies, including oil, gas, metals, and shipping markets
Practical AI in finance: Shape how AI is applied for automation, decision support, and commercial advantage in a fast-paced trading environment
Agentic systems: Build directly with cutting-edge agentic frameworks and access to frontier model capabilities
A degree in a technical field (Computer Science, Engineering, Mathematics, or related), with 3 to 5 years of professional experience in software, data, or AI engineering
Fluency in Python: Ability to write clean, modular, well-documented code, with strong understanding of engineering best practices
Familiarity with AI and LLMs: you understand how language models work and have built with them, including hands-on experience with prompting and agentic patterns (tool use, function calling, or MCP)
Familiarity with Git and version control workflows
Familiarity with Docker, containerization concepts
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 quickly picks up new domains
Curiosity for emerging AI developments, with a proactive commitment to continuously learning, experimenting and expanding your skills
Intellectual curiosity about commodities markets, global energy flows, and the commercial dynamics of trading; willingness to develop deep domain knowledge as part of the role
Additional Information
Independent and self-organized, able to manage your own time and priorities with minimal oversight
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 building MCP servers or clients, RAG pipelines, or multi-agent systems is advantageous
Experience with prompt engineering and developing reusable AI Skills
Familiarity with cloud platforms (e.g. AWS, Azure, or GCP)
Some knowledge of, experience with, or interest in quantitative finance and derivative markets
Prior work on LLM evaluations (evals) or model benchmarking is a plus

Employment type
Full-time

Work arrangement
No