At a Glance
- Tasks: Build AI-driven trading analytics and optimise data pipelines in a fast-paced environment.
- Company: Leading commodities trading house with a focus on innovation and collaboration.
- Benefits: Competitive daily rate, hybrid work model, and opportunity for long-term engagement.
- Other info: Fast turnaround for interviews; ideal for those eager to advance their careers.
- Why this job: Join a critical AI initiative and make an impact in the commodities trading sector.
- Qualifications: Strong Databricks and Spark experience, plus a solid foundation in statistics and econometrics.
Role: AI Engineer
Project: AI-driven trading analytics & data platforms
Industry: Commodities trading
Location: London (hybrid - 3 days onsite)
Contract: 6 months initial (multiyear scope)
Rate: £800-900/d (inside IR35)
X4 Technology are partnered with a leading commodities trading house, seeking a Contract AI Engineer to work directly with traders and analysts to build AI-powered analytics across pricing, fundamentals and risk using Databricks and modern data/LLM tooling. This role sits across data engineering, applied AI and front-office trading - turning trading requirements into production-ready analytics, models and agent workflows delivered at speed. You’ll operate in a fast-paced environment where prototyping, trader collaboration and production-grade engineering are equally critical. Hybrid role with close collaboration across trading and analytics teams, with a strong bias to rapid iteration and user feedback. Strong engineering discipline is required across CI/CD, testing and observability, alongside robust data governance and secure handling of sensitive data (including PII via Unity Catalog).
Responsibilities:
- Deliver AI-driven trading analytics (forecasting, seasonality, correlation, regression, scenario modelling)
- Build and optimise Databricks data pipelines (PySpark, Spark SQL, Delta Lake, Unity Catalog)
- Analyse large market and fundamentals time-series datasets using statistical and econometric methods
- Work directly with traders/analysts to turn requirements into usable tools and insights
- Build LLM/agent workflows (prompting, LangGraph, MCP, tool use, retrieval, guardrails)
- Productionise solutions with CI/CD, testing, observability and documentation
- Ensure secure, governed data practices (Unity Catalog, PII handling) and platform reliability
- Apply time-series methods and understand trading data (curves, fundamentals, pricing sources)
Requirements:
- Strong hands-on Databricks & Spark experience (PySpark, SQL, Delta Lake, Unity Catalog) with solid data engineering skills across ingestion, modelling, orchestration and performance tuning
- Strong statistical/econometric foundation applied to financial or time-series data
- Experience building LLM/agent systems (prompting, retrieval, LangGraph, MCP, tool use)
- Familiarity with CI/CD, Terraform, MLflow, feature stores, vector databases and modern data governance practices
- Experience in commodities or financial trading environments, with understanding of market microstructure, fundamentals and risk, plus exposure to front-office or trading desk workflows
Interviews are being scheduled immediately, with a fast turnaround expected for suitable candidates. This is a high-priority hire within a critical trading and AI initiative, and the client is keen to move quickly for strong profiles. If you’re excited to hearing more, please apply now for immediate consideration.
Contract AI Engineer (Commodities) in London employer: X4 Technology
Join a leading commodities trading house in London as a Contract AI Engineer, where you'll thrive in a dynamic hybrid work environment that fosters collaboration between traders and analysts. With a strong emphasis on innovation and rapid iteration, this role offers competitive rates and the opportunity to work on cutting-edge AI-driven analytics, ensuring your skills are honed in a fast-paced, supportive culture that prioritises employee growth and development.
StudySmarter Expert Advice🤫
We think this is how you could land Contract AI Engineer (Commodities) in London
✨Tip Number 1
Network like a pro! Reach out to folks in the commodities trading space, especially those who work with AI. A friendly chat can open doors and give you insights that job descriptions just can't.
✨Tip Number 2
Show off your skills! If you've got a portfolio or any projects related to AI-driven analytics, make sure to highlight them during interviews. Real-world examples can set you apart from the crowd.
✨Tip Number 3
Prepare for technical challenges! Brush up on your Databricks and Spark skills, and be ready to tackle some coding problems. The more confident you are, the better you'll perform under pressure.
✨Tip Number 4
Apply through our website! We’re always on the lookout for talent like yours. Plus, applying directly can sometimes speed up the process and get you noticed quicker.
We think you need these skills to ace Contract AI Engineer (Commodities) in London
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Contract AI Engineer role. Highlight your experience with Databricks, Spark, and any relevant projects that showcase your skills in AI-driven analytics and data platforms.
Craft a Compelling Cover Letter:Your cover letter should tell us why you're the perfect fit for this role. Mention your hands-on experience with LLM systems and how you've collaborated with traders or analysts in the past to deliver impactful solutions.
Showcase Your Technical Skills:Don’t forget to include specific examples of your technical skills, especially around CI/CD, testing, and observability. We want to see how you’ve applied these in real-world scenarios, particularly in fast-paced environments.
Apply Through Our Website:We encourage you to apply through our website for the best chance of getting noticed. It’s the quickest way for us to see your application and get you in the running for this exciting opportunity!
How to prepare for a job interview at X4 Technology
✨Know Your Tech Inside Out
Make sure you’re well-versed in Databricks, PySpark, and Spark SQL. Brush up on your data engineering skills and be ready to discuss how you've built and optimised data pipelines in the past. The more specific examples you can provide, the better!
✨Understand the Trading Landscape
Familiarise yourself with commodities trading and the specific challenges traders face. Be prepared to discuss how your AI-driven analytics can directly impact trading decisions. Showing that you understand market microstructure and risk will set you apart.
✨Demonstrate Your Problem-Solving Skills
Expect to tackle real-world scenarios during the interview. Think about how you would turn trading requirements into production-ready analytics. Practice explaining your thought process clearly and concisely, as this will showcase your ability to collaborate with traders and analysts.
✨Highlight Your CI/CD Experience
Since this role requires a strong engineering discipline, be ready to discuss your experience with CI/CD, testing, and observability. Share examples of how you've implemented these practices in previous projects, especially in fast-paced environments.
