Backend Software Engineering Intern

About Enterpret

Enterpret is building an AI-native customer intelligence platform that transforms large volumes of raw customer feedback into structured, queryable information. Its engineering work involves natural language processing, serverless computing, real-time analytics and scalable infrastructure.

The company says its investors include Kleiner Perkins and Sequoia Capital, and its customers include Canva, Notion and Wispr Flow.

Role overview

Enterpret is looking for a Backend Software Engineering Intern to contribute to production systems and AI-powered product features. Interns work alongside experienced engineers, participate in system design discussions, develop backend components and help build proof-of-concepts for AI integrations.

The internship emphasizes ownership, practical engineering, scalable systems and learning through real production work.

Key responsibilities

Participate in system design and implementation discussions.

Develop solutions from concept through production with engineering guidance.

Build scalable backend components using serverless architectures on AWS.

Help create proof-of-concepts for backend and AI feature integrations.

Work on integrations connecting model outputs with real-time inference.

Collaborate with engineers building the company's AI-native platform.

Debug issues and improve system speed, reliability and resilience.

Required qualifications

Willingness and ability to work on-site at the Bengaluru office.

Currently pursuing a degree in Computer Science or Engineering at a Tier 1 college.

Strong programming fundamentals in at least one modern programming language.

At least one prior internship in a relevant engineering, backend or AI role.

Genuine interest in distributed systems, serverless computing and AI-powered products.

Strong problem-solving, debugging and analytical skills.

Eagerness to learn how backend architecture supports AI features from model training to real-time inference.

Key technical skills

• Backend development
• Strong programming fundamentals
• AWS and serverless architecture
• Distributed systems
• AI/ML feature integration
• Real-time inference
• Debugging and problem-solving
• System design fundamentals