Vitol is a leader in energy and commodities. Vitol produces, manages and delivers energy and commodities to consumers and industry worldwide. In addition to its primary business of trading, Vitol is invested in infrastructure globally, with $10+billion invested in long-term assets.
Vitol’s customers include national oil companies, multinationals, leading industrial companies and utilities. Founded in Rotterdam in 1966, today Vitol serves its customers from some 40 offices worldwide. Revenues in 2023 were $400bn.
Our people are our business. Talent is precious to us and we create an environment in which individuals can reach their full potential, unhindered by hierarchy. Our team comprises more than 65+ nationalities and we are committed to developing and sustaining a diverse work force.
Learn more about us here.
Job Description
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
- 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.
Skills Required
- Degree in Computer Science, Engineering, Mathematics, or a related technical field
- 3 to 5 years of professional experience in software, data, or AI engineering
- Fluency in Python and understanding of software engineering best practices
- Hands-on experience with AI and large language models, including prompting and agentic patterns such as tool use, function calling, or MCP
- Familiarity with Git and version control workflows
- Familiarity with Docker and containerization concepts
- Exposure to modern full-stack development practices
- Ability to engage with non-technical end-users and understand their needs
- Strong communication, questioning, learning, and domain-adaptation skills
- Ability to work independently, self-organize, and manage priorities with minimal oversight
- Experience building products or shipping projects
- Experience with MCP servers or clients, RAG pipelines, or multi-agent systems
- Experience with prompt engineering and reusable AI Skills
- Familiarity with AWS, Azure, or GCP
- Knowledge of or interest in quantitative finance and derivative markets
- Experience with LLM evaluations or model benchmarking
- Proficiency in Excel
What We Do
Vitol is a global energy and commodities company that trades and distributes energy safely and responsibly, utilizing its logistical expertise and infrastructure network. It operates across the energy spectrum, including oil, gas, power, renewables, and metals.
