Security Software Engineer Project Intern (Product Security) - 2026 Start (BS/MS)

TikTok Inc.; San Jose (CA); On-site; USD 28,000 - 39,000; Part time

Job summary

TikTok Inc. is seeking a project intern to participate in security assessments and tooling projects, with opportunities to impact AI tooling and security reviews. You will engage in fast‑paced, hands‑on experiences, collaborate across teams, and gain exposure to strategic security initiatives at scale.

The internship offers practical on‑the‑job learning and aims to build deeper insight into your cybersecurity career interests, with rolling reviews and a minimum three‑month commitment.

Qualifications

• Pursuing a degree in CS/CE/IS or related STEM field.
• Experience in threat modeling, security tooling or privacy engineering.
• Knowledge of web/mobile/network security, OS internals, cryptography or cloud computing.
• Experience coding in JavaScript, Go, Python, Java, C++, or Rust.
• Strong problem solving and debugging skills.

Responsibilities

• Participate in security assessments such as pentests on web or mobile apps.
• Contribute to tooling projects with a security focus, including code review and API testing.
• Assist in building evaluators and optimisations for security review tooling.
• Improve LLM usage in the SDLC and enhance infrastructure security.

Skills

Security engineering

Threat modeling

Code review

API testing

NLP/LLM

Education

Pursuing CS/CE/IS degree

Tools

JavaScript (Node JS)

Go

Python

Java

C++

Rust

Job description

Responsibilities

About the Team

The team is missioned to build infrastructures, platforms and technologies, as well as to support cross-functional teams to protect our users, products and infrastructures. In this team you'll have a unique opportunity to have first‑hand exposure to the strategy of the company in key security initiatives, especially in building scalable and secure‑by‑design systems and solutions. Our challenges are not your regular day‑to‑day technical problems; you'll be part of a team that's developing new solutions to new challenges of a kind not previously addressed by big tech. It's working fast, at scale, and we're making a difference.

As a project intern, you will have the opportunity to engage in impactful short‑term projects that provide you with a glimpse of professional real‑world experience. You will gain practical skills through on‑the‑job learning in a fast‑paced work environment and develop a deeper understanding of your career interests.

Applications will be reviewed on a rolling basis - we encourage you to apply early.

Successful candidates must be able to commit to at least 3 months long internship period.

Responsibilities:

• Participate in security assessments such as pentests on Web or mobile applications.
• Take part in tooling development projects with a security focus, such as code review and API testing. Tools developed will benefit LLM integration.
• Assist in building Evals, harnesses and optimisations on existing AI tooling & systems for Security Review.
• Improve the usage of LLM in the SDLC process and enhance the infrastructure security.

Qualifications

Minimum Qualifications

• Undergraduate, or Postgraduate who is currently pursuing a degree/master in Computer Science, Computer Engineering, Information Systems or other STEM disciplines
• Security engineering experience such as threat modeling, security mitigation development, security tooling development or privacy engineering.
• Understanding in various disciplines: web application security, mobile app security, network security, operating system internals and hardening, applied cryptography, cloud computing. You're expected to be an expert in at least one of these areas.
• Experience in writing and reviewing code in at least one of the following programming languages: JavaScript (Node JS), Go, Python, Java, C++, Rust.
• Strong problem‑solving skills and excellent debugging / troubleshooting skills.

Preferred Qualifications

• Experience with NLP/LLM
• Knowledge of distributed systems, edge computing, or high‑performance network programming

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