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Security Software Engineer: AI & Platform Defense

Job in San Jose, Santa Clara County, California, 95199, USA
Listing for: ByteDance
Full Time position
Listed on 2026-11-02
Job specializations:
  • Software Development
    AI Engineer (Applied/Software)
Salary/Wage Range or Industry Benchmark: 120000 - 170000 USD Yearly USD 120000.00 170000.00 YEAR
Job Description & How to Apply Below
AI Agent Security Software Engineer Graduate (Security Engineering) - 2027 Start

Location:

San Jose

Team:

Security

Employment Type:

Regular

Job Code:

A61751C

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Responsibilities

The Security Engineering team at Byte Dance builds and operates the core systems that protect one of the world's largest internet platforms and its global user community. We tackle challenges that span threat detection and response (TDR), infrastructure protection, and the emerging frontier of AI and LLM system security — all at the scale of Tik Tok and Byte Dance. Our engineers combine deep systems-building expertise with strong security fundamentals to deliver high-impact, production-grade solutions in a fast-paced, globally distributed environment.

If you thrive on ownership, love solving ambiguous problems, and want your work to safeguard products used by billions, this is the team.

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Online Assessment Candidates who pass resume screening will be invited to participate in Our Company's technical online assessment.

Responsibilities
- Build and iterate on threat detection, prevention, and response (TDR) systems for large-scale platforms, critical infrastructure, and globally distributed endpoints.

- Support the security of LLM-based systems and AI agent systems by identifying attack surfaces, developing defensive mechanisms, and improving safe deployment.

- Contribute to rapid exploration in LLM and AI agent security through prototyping, evaluation, security analysis, machine learning, and AI agentic approach.

- Develop, test, deploy, and improve distributed security systems with a focus on reliability, observability, and scalability.

- Work with cross-functional teams to translate product and security needs into engineering solutions and deliver impactful security capabilities.

Qualifications

Minimum Qualifications
- Individuals who are completing or have recently completed a Bachelor's degree in Computer Science, Computer Engineering, Cybersecurity or a related discipline.

- Solid fundamentals in computer science, including algorithms, data structures, operating systems, computer networks, and databases.

- Proficiency in at least one programming language such as Go, Java, Rust, Python, or C++, with the ability to write clean, reliable, and maintainable code.

- Foundational understanding of back-end development, distributed systems, or cloud-native infrastructure through coursework, internships, research, or project experience.

- Strong problem-solving skills, with the ability to think critically, break down complex problems, and learn quickly in a fast-evolving technical environment.

Preferred Qualifications
- Internship, research, or project experience building AI/LLM applications, AI agent systems, or related back-end and distributed systems.

- Familiarity with core security concepts such as authentication, authorization, threat detection, vulnerability mitigation, and secure system design.

- Research experience, or strong technical understanding, in the security of LLM-based systems and AI agent architectures, including areas such as prompt injection, tool misuse, model abuse, and agent workflow security.

-…

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