Contract AI Engineer (Commodities)

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 of the Contract AI Engineer (Commodities)

• 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 for the Contract AI Engineer (Commodities)

• 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.