Trafigura
Applied AI Engineer

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Main Purpose
Trafigura is undergoing an exciting Digital Transformation, developing innovative AI technologies to change the way we work in Commodities Trading. The Document AI team is a key pillar of this initiative, unlocking data-rich proprietary documents to enable high-value process optimisation and data science use cases.
We are seeking an Applied AI Engineer to grow our Document AI platform, developing robust and scalable AI solutions that solve real business problems. As a document intensive industry, you will be building production-ready Agentic AI/LLM systems that radically transforms Commodities Trading.
This is a hands-on Individual Contributor role.
Required Qualifications
- 5-8+ years of experience building production AI/ML systems
- Modern Python proficiency with deep knowledge of the ecosystem (Pydantic, FastAPI, asyncio, type safety)
- Experience with modern AI frameworks (we currently favour Pydantic AI)
- Production experience maintaining human-in-the-loop systems and AI monitoring/observability
- Strong fundamentals in AI/ML evaluation frameworks
- Experience building agentic systems including MCP, tool calling, memory systems, vector-based knowledge stores, guardrails
- In-depth understanding of modern software design principles (e.g. microservices, event-driven architectures, domain driven design, object-oriented programming, test-driven development)
- In-depth understanding of modern software development lifecycle (CI/CD, IaC, Containerisation)
- Practical experience with cloud engineering (preference for AWS)
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Grad scheme, placement, apprenticeship? Not sure what you want yet — that's fine. Your agent talks it through with you and turns "I have no idea" into a shortlist.
Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
See breakdownIt searches the market for you
Every day your agent scans the market matching roles against what actually matters to you, not just keywords on a CV.
Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
Only hits
No noise. No "maybe this fits." Just roles with a clear explanation of why they're right — and where to focus when applying.
Preferred Qualifications
- Prior experience in Commodities, Fixed Income, Equities, Asset Management is a plus
Key Responsibilities
- Develop and maintain Python-based AI applications
- Build and maintain document workflows using LLMs and classical NLP
- Debug model performance issues, handle edge cases, and optimize system reliability
- Write comprehensive tests and implement monitoring for AI/ML systems
- Rapidly prototype new features, evaluate them, and implement to production
- Participate in code reviews, technical design discussions, and architecture decisions
- Communicate effectively with both technical and non-technical stakeholders to understand and translate business requirements into production code
Example projects you might own in the first 6 months include:
- Develop a specialised agent to automate highly complex commodity trading workflow
- Develop an agent to operate within human workflows, including seamless UI integrations and long-running durable executions
- Develop a new AI product to extract key insights from firmwide market intelligence emails for front and middle office
Attributes for Success
- Engineering mindset focused on delivering practical solutions that solve real business problems
- Self-directed and comfortable working autonomously with minimal supervision
- Pragmatic approach to technology choices - you pick the right tool for the job rather than chasing trends
- Deep appreciation for AI system reliability - you understand that making AI systems work consistently is the hardest part of the job
- Intellectually curious and adaptable to rapidly evolving AI/ML landscape
- Strong desire to help people solve problems


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Key Relationships
- You will work closely with the Digital Transformation Team to understand business requirements and rollout production-grade applications to solve them.
- You will support the Data Science & Engineering teams as a Centre of Excellence for Agentic AI and related tech, providing support in the form of knowledge sharing and tool adoption.
Department Overview
The Digital Transformation Team is a joint venture between Trading Technology and the Data Science and Engineering Team, driving Trafigura's AI-powered evolution in commodities trading. As a Centre of Excellence for Agentic AI, we develop scalable applications that impact over 5,000 employees daily, supporting both immediate business needs and broader data science initiatives across Trafigura's global operations.
Reporting Structure
You will report directly to the Document AI Lead.
Equal Opportunity Employer
We are an Equal Opportunity Employer and take pride in a diverse workforce. We do not discriminate in recruitment, hiring, training, promotion, or other employment practices for reasons of race, colour, religion, gender, sexual orientation, national origin, age, marital or veteran status, medical condition or handicap, disability, or any other legally protected status.
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