AI Engineering Intern

Role Overview

• Support the team in identifying and exploring potential AI use cases, including basic research to inform buy-vs-build discussions.
• Assist in designing and delivering AI prototypes, contributing across problem definition, experimentation, and pilot stages.
• Help build AI-powered features and components under the guidance of senior engineers.
• Contribute to the development of datasets, retrieval pipelines, and reasoning workflows across different business functionalities.
• Explore integrations with vendor AI platforms and internal AI solutions, learning to reuse existing capabilities where possible.
• Help instrument solutions to track adoption, quality, and performance metrics.
• Collaborate with the technology team to learn how secure, compliant, and supportable solutions are built.

Requirements

• Currently pursuing or recently completed a Bachelor's in Computer Science, Data Science, Artificial Intelligence / Machine Learning, Software Engineering, or a related discipline.
• Interest in the financial industry and a curiosity to learn about financial markets (prior exposure is a plus, not a requirement).
• Some practical experience with ML/AI concepts through coursework, personal projects, hackathons, internships, or open-source contributions.
• Awareness of cloud platforms (AWS preferred); any AWS learning paths or certifications are a plus.
• Working proficiency in a modern programming language, ideally Python.
• Familiarity with databases such as PostgreSQL, MS SQL, Snowflake, or similar—through coursework or projects.
• Foundational understanding of how to build software applications (e.g., Python, APIs, basic system integration, testing).
• Exposure to teamwork on software projects, with an appreciation for code quality, good design, and collaboration.
• Familiarity with the software development lifecycle, version control (e.g., Git), and an interest in modern DevOps practices.
• Ability to break down ambiguous problems into smaller tasks and communicate progress clearly.
• Awareness of the importance of working responsibly with sensitive/confidential data, and a willingness to learn about governance, risk, and security practices.
• Strong collaboration and communication skills—comfortable asking questions and working with people across business and technology teams.
• Driven, curious, self-starter with an inclusive, team-oriented mindset and eagerness to learn.

Tech Stack

• AWS
• Cloud
• Postgres
• Python
• SQL

Benefits

• A professional, international, and high performing work environment
• The opportunity to work within a matrix organization alongside cross-functional, international stakeholders
• Exposure to multiple private market asset classes, including private equity, infrastructure, real estate, credit, and royalties
• A collaborative environment with on-the-job training and mentorship opportunities
• Participation in enjoyable office and team events, including volunteering activities that support local communities