Front Office Software Engineer Internship (Summer 2027)

Program Summary - Data Science & Technology Internship

Application Deadline: September 1st, 11:59pm EST

Company Overview

Castleton Commodities International is a leading global energy commodities merchant and infrastructure asset investor. As a trader, CCI deploys capital on a proprietary basis in the physical and financial commodity markets, providing the company with market insights and access. As a strategic investor and developer, CCI leverages its market expertise, operations capabilities, and industry knowledge to invest in and develop select commodity infrastructure assets. Since its formation, CCI’s strategically integrated platform has generated strong risk-adjusted returns for its investors.

Position Overview

CCI is developing a leading-edge analytics platform, and staying at the forefront of data management and analytics is essential to its investment strategy. The company is seeking motivated and detail-oriented Front Office Software Engineering Interns to join its Global Data Science & Technology team in its London office.

This internship is ideal for technically skilled students with a strong interest in building quality software that directly impacts trading, analytics, and investment workflows. You will collaborate closely with other software engineers, data scientists, and commercial end users, contributing to the front office platform through hands-on development projects using Python, cloud technologies (AWS), APIs, and Snowflake.

Responsibilities

• Contribute to the development of front office software tools that support real-time trading, market data analytics, and visualization.
• Work with the commercial trading team to optimize and re-engineer pricing models, decision tools, and trading workflows.
• Build and enhance Python-based microservices and APIs for internal data access and operations automation.
• Assist in building data visualization dashboards using libraries such as Streamlit, integrating commercial KPIs, price curves, and supply/demand analytics.
• Participate in cloud-native application development using AWS services, including Kubernetes and Kafka.
• Support automation of deployment processes using modern DevOps tools (e.g., Git, Docker, Helm, CI/CD pipelines).
• Collaborate with the Data Science team to integrate ML-driven analytics into front office workflows.

Qualifications

• Currently pursuing a Bachelor’s or Master’s degree in Computer Science, Engineering, Management Information Systems, or a related technical field.
• Strong programming experience in Python (preferred libraries: Pandas, NumPy, etc.).
• Familiarity with version control tools (e.g., Git) and software development best practices.
• Strong problem-solving abilities and an eagerness to learn about financial markets and trading systems.
• Excellent communication skills and ability to work in a fast-paced, collaborative environment.