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JobsPerplexity AI

Internship - Search Backend Infra Engineer

Perplexity AI

Internship - Search Backend Infra Engineer

Perplexity AI

Belgrade

·

On-site

·

Internship

·

1w ago

Required Skills

Go

Rust

C++

Backend Engineering

Infrastructure

Perplexity is looking for a Backend/Infrastructure Engineer Intern to support our small, high-impact team building the systems that power our search experience. You will work closely with experienced engineers to help design, build, and operate robust infrastructure and backend services that keep Perplexity fast, reliable, and scalable.

Internship program: 12 - 24 weeks, full-time, in-person in the Belgrade office.

Responsibilities:

  • Build and maintain infrastructure that supports high-performance search systems, with mentorship from senior engineers.

  • Design internal tools and automation to improve developer workflows and operational efficiency.

  • Support the design, deployment, and monitoring of cloud-native systems on AWS.

  • Contribute to improving CI/CD pipelines, testing infrastructure, and release processes.

  • Debug and optimize Linux-based services, containers, and backend systems.

  • Contribute to product codebases, primarily using Rust, Go or C++.

Qualifications:

  • Working towards a degree in Computer Science, Engineering, or a related field, or equivalent practical experience.

  • Familiarity with at least one programming language such as Go, Rust, or C/C++, through coursework or projects.

  • Basic understanding or exposure to cloud infrastructure (e.g. AWS) and Linux systems is a plus, not a requirement.

  • Interest in infrastructure, distributed systems, or backend engineering, with willingness to learn about CI/CD, monitoring, and performance.

  • A proactive and curious learner who enjoys collaborating in a fast-paced, innovative environment

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About Perplexity AI

Perplexity AI

Perplexity AI, Inc., or simply Perplexity, is an American privately held software company offering a web search engine that processes user queries and synthesizes responses.

51-200

Employees

San Francisco

Headquarters

$1B

Valuation

Reviews

4.0

1 reviews

Work Life Balance

3.0

Compensation

3.0

Culture

3.0

Career

3.5

Management

3.0

70%

Recommend to a Friend

Pros

Helpful tool for research and analysis

Useful for job application preparation

Effective for complex marketing challenges

Cons

Limited feedback provided

No specific criticisms mentioned

Insufficient detail on potential drawbacks

Salary Ranges

28 data points

Junior/L3

Junior/L3 · LLM Teacher

1 reports

$101,920

total / year

Base

$78,400

Stock

-

Bonus

-

$101,920

$101,920

Interview Experience

1 interviews

Difficulty

4.0

/ 5

Duration

14-28 weeks

Experience

Positive 0%

Neutral 0%

Negative 100%

Interview Process

1

Application Review

2

HR Screen

3

Take-home Marketing Challenge

4

Hiring Manager Interview

5

Panel Interview

6

Offer

Common Questions

Digital Marketing Strategy

Campaign Performance Analysis

Behavioral/STAR

Technical Marketing Knowledge

Case Study