AI-Driven Software Engineer Intern (Summer 2027)

Engg; New York (NY); On-site; USD 85,000 - 99,000; Full time

Job summary

Harvey is recruiting a Software Engineer Intern (Summer 2027) to join our Engineering team. You will collaborate with Product, AI, Legal, and GTM teams to build secure, intuitive systems powering our AI products.

This 12 or 16 week internship is ideal for curious, motivated students learning modern application-layer and GenAI products. Expected to learn across the stack and contribute real features in production.

Qualifications

• Enrolled in a Bachelor's or Master’s program in computer science, engineering, or a related field with graduation date of December 2027 or later.
• Able to work from New York or San Francisco offices during the summer cohort; relocation support is available.
• Previous internship experience is required.
• Strong proficiency in one or more programming languages (Python, TypeScript/JavaScript, Java, Go) and solid CS knowledge.

Responsibilities

• Own a project end-to-end from coding and testing to deploying it to production, and present your work to peers and leaders.
• Write clean, maintainable code that meets the team’s standards and use AI-assisted development tools.
• Build knowledge of the systems you support and the users they serve, contributing to product discussions.
• Collaborate through code reviews, pair programming, design reviews and technical documentation.
• Depending on the team, contribute to retrieval over large document collections, interfaces for AI systems, multi-region compute infrastructure, or secure systems for client data.

Skills

Python

TypeScript/JavaScript

Java

Go

Education

Bachelor's or Master's in CS/Engineering

Tools

Claude Code

Codex

Cursor

Job description

Harvey is recruiting a Software Engineer Intern (Summer 2027) to join our Engineering team. You will collaborate with Product, AI, Legal, and GTM teams to build secure, intuitive systems powering our AI products.

This 12 or 16 week internship is ideal for curious, motivated students learning modern application-layer and GenAI products. Expected to learn across the stack and contribute real features in production.