Senior AI Security Engineer

TeamViewer US, Inc.
Austin, TX, United States
4 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Working hours
Regular working hours

Tech stack

Java (Programming Language) Artificial Intelligence User Authentication C Sharp (Programming Language) C++ (Programming Language) Cyber Security Computer Programming Distributed Systems Python (Programming Language) Network Security Open Web Application Security Systems Development Life Cycle
+8 more
Secure Coding Systems Integration TeamViewer Web Applications Cloud Platform System Large Language Models AI Platforms Golang

Job description

Experteer Overview In this role, you own the security architecture of TeamViewer’s AI platform, shaping secure agent integrations, permissions, and auditing. You will identify risks, design controls, and strengthen the AI development lifecycle across engineering teams. You’ll lead red-team exercises and collaborate with product and engineering to embed security by design, delivering training on secure AI practices. This is a chance to impact customer endpoints and tenant data at scale in a diverse, innovative environment. Compensation / Benefits * Own the security architecture of the AI platform, including agent integrations, tool access, and context management * Identify and mitigate AI security risks such as prompt injection, unauthorized tool use, and data exposure * Design and implement permission, approval, and auditing frameworks for AI-driven actions * Build security controls into products and development processes for scalable adoption * Secure the AI development lifecycle (generated code, dependencies, secrets, reviews) * Lead red-team exercises and adversarial testing of AI capabilities * Partner with product and engineering teams to provide security guidance and best practices * Develop and deliver training on secure coding, AI security, and responsible AI development Tasks * 7+ years in product, application, or platform security with emphasis on AI and agent-based systems * Deep understanding of AI security risks and mitigation strategies (OWASP Top 10 for LLM Applications) * Hands-on security testing, red-teaming, and adversarial evaluations of AI systems * Programming in C++, with familiarity in Java, C#, Go, and Python for security tooling * Strong knowledge of web applications, distributed systems, authentication, authorization, cryptography, and network security * Experience integrating security throughout the SDLC and collaborating with engineering teams * Experience mentoring engineers and promoting security best practices across distributed teams * Strong communication, collaboration, and problem-solving skills Key requirements * Competitive compensation and bonuses * Flexible PTO and paid holidays * 401(k) with employer matching * Comprehensive Health insurance package including 100% employer-paid medical coverage * Up to 12 weeks of Parental Leave * Life Insurance, Short-Term & Long-Term Disability, 100% employer-paid

Requirements

_ Strong communication, collaboration, and problem-solving skills Key requirements * Competitive compensation and bonuses * Flexible PTO and paid holidays * 401(k) with employer matching * Comprehensive Health insurance package including 100% employer-paid medical coverage * Up to 12 weeks of Parental Leave * Life Insurance, Short-Term & Long-Term Disability, 100% employer-paid

About the company

Experteer Overview In this role, you own the security architecture of TeamViewer’s AI platform, shaping secure agent integrations, permissions, and auditing. You will identify risks, design controls, and strengthen the AI development lifecycle across engineering teams. You’ll lead red-team exercises and collaborate with product and engineering to embed security by design, delivering training on secure AI practices. This is a chance to impact customer endpoints and tenant data at scale in a diverse, innovative environment. Compensation / Benefits * Own the security architecture of the AI platform, including agent integrations, tool access, and context management * Identify and mitigate AI security risks such as prompt injection, unauthorized tool use, and data exposure * Design and implement permission, approval, and auditing frameworks for AI-driven actions * Build security controls into products and development processes for scalable adoption * Secure the AI development lifecycle aa

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