GenAI Engineer

About the role

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

Qualifications & Requirements

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

Comprehensive benefit coverage includes

Medical Dental Vision Paid Vacation 401k with company contributions Life insurance Short-term & Long-term disability All your information will be kept confidential according to EEO guidelines.