At a Glance
- Tasks: Develop and maintain innovative AI solutions for Commodities Trading.
- Company: Join Trafigura, a leader in Digital Transformation and AI technologies.
- Benefits: Competitive salary, diverse workforce, and opportunities for professional growth.
- Other info: Work in a dynamic environment with a focus on collaboration and innovation.
- Why this job: Make a real impact by transforming the way commodities trading operates with cutting-edge AI.
- Qualifications: 5-8+ years in AI/ML systems and strong Python skills required.
The predicted salary is between 70000 - 90000 £ per year.
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 transform 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)
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
- 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
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.
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.
Applied AI Engineer employer: Puma Energy
Trafigura is an exceptional employer that fosters a dynamic work culture where innovation meets practical delivery. As a Forward Deployed Engineer, you will have the opportunity to work closely with business stakeholders, driving meaningful technical deployments that directly impact business outcomes. With a strong emphasis on employee growth, collaboration, and cutting-edge technology, Trafigura offers a unique environment for professionals looking to make a significant difference in the financial services sector.
StudySmarter Expert Advice🤫
We think this is how you could land Applied AI Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your AI projects, especially those that align with the role. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common AI/ML questions and real-world problem-solving scenarios. Practice explaining your thought process clearly, as communication is key in tech roles.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Applied AI Engineer
Some tips for your application 🫡
Tailor Your CV:Make sure your CV reflects the skills and experiences that match the job description. Highlight your Python proficiency and any experience with AI frameworks, as these are key for us at Trafigura.
Craft a Compelling Cover Letter:Use your cover letter to tell us why you're passionate about AI in Commodities Trading. Share specific examples of how you've solved real business problems with AI/ML systems in the past.
Showcase Your Projects:If you've worked on relevant projects, especially those involving document workflows or agentic systems, make sure to include them. We love seeing practical applications of your skills!
Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you don’t miss out on any important updates from our team.
How to prepare for a job interview at Puma Energy
✨Know Your AI Stuff
Make sure you brush up on your knowledge of AI frameworks, especially Pydantic AI. Be ready to discuss your experience with building production AI/ML systems and how you've tackled real business problems in the past.
✨Show Off Your Python Skills
Since modern Python proficiency is a must, prepare to demonstrate your skills with libraries like FastAPI and asyncio. You might even be asked to solve a coding challenge, so practice writing clean, efficient code that adheres to best practices.
✨Understand the Business Side
Get familiar with the commodities trading industry and how AI can optimise processes within it. Being able to communicate effectively with both technical and non-technical stakeholders will set you apart, so think about how you can translate complex concepts into simple terms.
✨Be Ready for Problem-Solving
Expect to discuss how you've debugged model performance issues and handled edge cases in previous roles. Prepare examples that showcase your engineering mindset and your ability to deliver practical solutions that solve real business problems.
