Product Security - AI DevOps Engineer - Global Security Organisation

Responsibilities

The mission of TikTok's Global Security Organization is to build and earn trust by reducing risk and securing our businesses and products. Also known as "GSO", this team is the foundation of our efforts to keep TikTok safe, secure, and operating at scale for over 1 billion people around the world. We work to ensure that the TikTok platform is safe and secure, that our users' experience and their data remains safe from external or internal threats, and that we comply with global regulations wherever TikTok operates.

Trust is one of TikTok's biggest initiatives, and security is integral to our success. In whatever ways users interact with us - whether they're watching videos on their For You page, interacting with a Live video, or buying products on TikTok Shop - GSO protects their data and privacy, so they can have a secure and trustworthy experience.

The GSO provides industry-leading security and privacy services to Bytedance, guided by four principles: trust and transparency, business enablement, risk-informed decision-making, and proactive risk reduction. We strive to build sustainable, world-class security capabilities.

SecOps Validation Team (STOV) is responsible for the tools and technologies that support the TikTok infrastructure. STOV oversees technical validation, security operations, and drives engineering enhancements, including the deployment, configuration, and maintenance of security technologies across various domains.
The role will be responsible for the design, development, and operation of AI/ML systems that enable Product Security technical controls required by security policy and regulations. Validation targets include the product security of the TikTok product family and the Secure SDLC process. This role will provide a solid foundation to evaluate and improve maturity across TikTok's product security practices and Secure SDLC.
A key responsibility is to operate and maintain the Large Language Model (LLM)-based product security validation system and knowledge base. This includes implementing DevOps/MLOps best practices to ensure reliable, scalable, and secure deployment, monitoring, and continuous improvement of the system.

RESPONSIBILITIES
- Build and maintain ML pipelines for training, deployment, and monitoring in production
- Develop APIs, integrations, and automation tools for AI-driven security validation workflows
- Design and manage CI/CD pipelines for LLM services and related security applications
- Operate and optimize vector databases, embeddings, and RAG pipelines
- Implement monitoring, logging, and incident response for AI/ML systems
- Collaborate with product security engineers to embed AI-driven controls into Secure SDLC
- Maintain and expand the LLM-based knowledge base for product security validation

Qualifications

Minimum Qualifications
- Experience in software development (Python, Go or Java)
- Strong experience with DevOPs/MLOps practices (CI/CD, Docker, Kubernetes, monitoring)
- Experience with cloud platforms and ML serving infrastructure
- Excellent problem-solving and analytical skills with focus on production reliability

Preferred Qualifications
- Bachelor's or Master's degree in Computer Science, AI/ML, Cybersecurity, or related fields
- Experience with LLMs and techniques like fine tuning, and retrieval-augmented generation (RAG).
- Operation knowledge on vector databases and text embedding models
- Solid experience in data engineering workflows and large scale data processing
- Certifications in Cloud (AWS ML Specialist, GCP ML Engineer) or Security (CISSP, CSSLP)
- Experience with model monitoring, A/B testing, and gradual deployment strategies
- Contribute to open-source DevOps, ML Ops or security projects