AI Engineer (Trading Analytics & Data Engineering)

Job Description:

Client is hiring an AI Engineer with a strong data engineering foundation and excellent communication skills-ideally with commodity or financial trading experience. Youll partner with traders and trading analysts to rapidly build AI powered analytics over market pricing and fundamentals data using Databricks and Spark to deliver value at speed.

Ways of working:

- Hybrid; high touch collaboration with trading teams.

- Bias to prototype fast iterate with users and harden to production.

- Maintain operational stability of production pipelines using secure modern CI/CD engineering practices - with automated testing quality gates and built in reliability across development security and operations.

Roles and Responsibilities:

- Design and ship AI driven analytics for front office use (seasonality correlation regression forecasting scenario modelling).

- Build reusable and scalable data pipelines in Databricks (PySpark/Spark Delta/Unity Catalog) optimizing cost reliability and performance.

- Run statistical/econometric analyses on large datasets (e.g. market & fundamental time series data).

- Collaborate directly with traders/analysts-translate ambiguous questions into shippable solutions; communicate insights clearly.

- Implement LLM/agentic workflows: prompt engineering LangGraph orchestration MCP integrations tool calling retrieval and guardrails.

- Productionize solutions with testing observability versioning and documentation.

Mandatory skills:

- Hands on Databricks Spark expertise (PySpark SQL Delta Unity Catalog).

- Proven data engineering skills (ingestion modelling orchestration performance tuning).

- Strong statistics/economics/data science fundamentals for market time series.

- Experience building LLM solutions (prompting retrieval agent flows; LangGraph MCP) and integrating with trading data/services.

- Experience with CI/CD Terraform MLflow/feature stores vector DBs and governance (PII handling data lineage).

- Excellent stakeholder skills; able to work on desk with traders/analysts and deliver fast.

Business Application:

- Background in commodity or financial trading.

- Familiarity with market microstructure supply demand fundamentals risk management.