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Enterpret

Transforms customer feedback into product insights

Backend Software Engineering Intern

Backend EngineeringConfirmed live in the last 24 hours
InternshipBengaluru, Karnataka, IndiaNo salary listed

About the Job

Requirements

  • Must be able and willing to work in person at the Bengaluru office.
  • Must be pursuing a degree in Computer Science or Engineering from a Tier 1 college.
  • Must have strong programming fundamentals in any modern language.
  • Must have completed at least one prior internship in a relevant engineering, backend, or AI role.
  • Must have a genuine interest in distributed systems, serverless computing, and AI-powered product features.
  • Must demonstrate problem-solving, debugging, and analytical skills.

Responsibilities

  • Join internal system design discussions and contribute ideas to design and implementation conversations.
  • Build solutions from concept to production with guidance.
  • Develop scalable backend components using serverless architectures on AWS.
  • Help build proof-of-concepts for new backend and AI feature integrations, from model output to real-time inference.
  • Work with engineers building the AI-native platform and learn how backend architecture supports AI features end to end.
  • Investigate system failures with the team and improve system speed and resilience.

Desired Qualifications

  • Open-source contributions or backend/AI project experience.

About the Company

Enterpret

Transforms customer feedback into product insights

Enterpret provides a customer feedback intelligence platform that helps product teams turn feedback into actionable insights. It collects feedback from multiple sources, unifies and categorizes it using adaptive AI into a Custom Unified Feedback Taxonomy, and enables precise, granular insights to prioritize product work. How it works: users access a user-friendly interface, build dashboards, and use semantic search to interpret the meaning across feedback, with automated summaries. Differentiators: adaptive taxonomy that evolves with feedback, semantic search across all feedback, and a structure that supports non-technical operators; the service includes dedicated data auditors for weekly model refreshes and a dedicated Customer Success Manager. Goal: help product companies build products centered on customer needs by continuously refreshing models and insights.

Company size
51-200
Company stage
Series A
Total funding
$25.1M
Headquarters
San Francisco, CA
Founded
2020

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