Product Engineer Intern

Hex•San Francisco, CA

62d•$11,000 - $11,000•Hybrid

About The Position

Hex is seeking a Product Engineer Intern to help build AI-powered data tools that let users understand and work with data using natural language and agentic AI. The intern will contribute to product features used by data teams to explore, analyze, and collaborate, and will learn from experienced engineers while shipping features to production. Prior AI experience is not required. The role works across the stack with mentors and in close collaboration with designers, product managers, and AI engineers. The intern will take part in the full development lifecycle, from ideation and design through implementation, testing, and launch. This is a hybrid position based in San Francisco, with three days per week in the office. The salary is $11,000 per month, plus a housing stipend.

Requirements

Pursuing a degree in Computer Science, Engineering, or a related field, with plans to graduate in December 2026 or 2027.
Full-stack engineering experience, ideally with JavaScript, TypeScript, and/or Python.
Built academic, personal, or professional projects demonstrating the ability to ship software.
Interest in AI-driven product experiences and eagerness to learn how AI agents, prompting strategies, and context engineering work in production systems.
Care about users and enjoy considering how technical systems translate into polished, intuitive experiences.
Curious, adaptable, and comfortable working in a fast-paced environment where priorities may shift.
Enjoy collaborating, asking questions, and learning from more senior engineers.

Responsibilities

Build product features across the stack using React, TypeScript, and/or Python for core workflows used by data practitioners.
Collaborate with AI engineers to prototype and refine agentic capabilities, explore prompting strategies, and improve model quality in user-facing experiences.
Design and improve end-to-end workflows for collaborative editing, data exploration, debugging, and AI-assisted development.
Address engineering challenges such as performance optimization, front-end user experience improvements, and API design for AI-driven features.
Participate in the full development lifecycle, from ideation and design through implementation, testing, and launch.