2027 Enterprise AI Intern

About the role

This Enterprise AI internship offers hands-on ownership of prioritized use cases, taking solutions from stakeholder requirements through design, build, testing, rollout, and adoption tracking. Based in New York City, the role uses shared AI infrastructure and offers potential full-time conversion for strong performers.

Responsibilities

• Own prioritized AI use cases from initial idea through user adoption and impact measurement.
• Gather and refine requirements with business stakeholders, then design, build, test, and launch solutions.
• Partner with Platform & Tools to use shared services, APIs, SDKs, and evaluation tooling.
• Provide feedback on platform capabilities based on use-case requirements.
• Work directly with business users and drive adoption of delivered solutions.

Internship and Training

• Complete a 10-week summer internship focused on real-world challenges and impactful solutions.
• Receive guidance from a dedicated manager and mentor throughout the internship and beyond.
• Attend senior-leader learning sessions, hands-on skills workshops, networking events, and peer social activities.
• Collaborate with senior team members in a fast-paced, technology-driven investment environment.

Required Qualifications

• Pursue a bachelor's, master's, or PhD in computer science, statistics, mathematics, physics, or electrical engineering.
• Ideally have one year remaining in your academic program.
• Demonstrate excellent Python programming skills and a working understanding of LLM-based applications.
• Understand prompting, retrieval, agents, model APIs, and when LLM solutions are appropriate.
• Translate ambiguous business problems into clear requirements and scoped, deliverable solutions.
• Demonstrate communication, creative problem-solving, attention to detail, and an end-to-end delivery mindset.

Preferred Qualifications

• Experience with Go, Java, or TypeScript is beneficial.
• Previous financial industry experience is welcomed but not required.
• Hands-on exposure to AWS, Azure, shared internal services, APIs, or SDKs is beneficial.
• Experience gathering requirements, testing projects with end users, and measuring post-launch usage is beneficial.