Software Engineer, Intern (Summer 2027)

at Glean
USD 57-69 per hour
INTERN
✅ Hybrid

Tech Stack

AI @ 3 API @ 3 LLM @ 3 Machine Learning NLP @ 3 Security @ 3 Software Development @ 6

Details

Glean is building a Work AI platform that combines enterprise search, an AI Assistant, scalable AI agents, enterprise and personal knowledge graphs, over 100 SaaS connectors, flexible LLM choice, and robust APIs.

As a Software Engineer intern, you will help design, develop, and maintain software solutions that power Glean's products and services.

Responsibilities

  • Own a scoped, high-impact project end to end, from defining the problem and writing a design through building, testing, launching, and measuring outcomes.
  • Ship reliable, well-tested, maintainable, production-quality code through thoughtful code reviews and iterative feedback.
  • Contribute across the stack based on your interests, including backend services, product engineering, ML/AI/search, infrastructure, security, and more.
  • Work closely with people within and beyond your team.

Requirements

  • Graduating in Fall 2026 or Spring 2027 with a B.S., M.S., or Ph.D. in Computer Science or an equivalent program.
  • Team-player attitude, a strong desire to learn, and an owner mentality.
  • Comfortable working in a fast-paced, data-driven environment.
  • Interest in backend, infrastructure, security, UI/full-stack, or ML/NLP/search.
  • Prior internship experience in one or more of these areas.
  • Strong foundation in computer science and software development fundamentals.

Location

  • Hybrid role requiring four days per week in either the Mountain View or San Francisco office.

Compensation and Benefits

  • Hourly pay range of $57–$69.
  • Certain roles may be eligible for variable compensation, equity, and benefits.
  • Glean is committed to an inclusive and diverse workplace and does not discriminate based on gender, ethnicity, sexual orientation, religion, civil or family status, age, disability, or race.
  • The interview process includes a brief AI-focused exercise or discussion about how candidates think about, design, and use AI.

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