Senior Engineer - AI Agentic Fuzzing & Linux Security

As a leading technology innovator, Qualcomm pushes the boundaries of what's possible to enable next-generation experiences and drives digital transformation to help create a smarter, connected future for all. As a Qualcomm Software Engineer, you will design, develop, create, modify, and validate embedded and cloud edge software, applications, and/or specialized utility programs that launch cutting-edge, world class products that meet and exceed customer needs. Qualcomm Software Engineers collaborate with systems, hardware, architecture, test engineers, and other teams to design system-level software solutions and obtain information on performance requirements and interfaces.

Minimum Qualifications:

• Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience.

OR

Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience.

OR

PhD in Engineering, Information Systems, Computer Science, or related field.

• 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc.

About the Role

We are looking for a Senior Security Engineer to contribute to the area of Linux platform security, with a focus on AI-driven automated fuzzing and continuous security assurance across embedded and mobile platforms. The person will be responsible for designing and deploying intelligent fuzzing infrastructure, developing fuzzing harnesses using agentic AI frameworks, performing security risk assessments, and conducting secure code reviews for Linux kernel and driver stacks.

The ideal candidate possesses a strong security-first mindset, hands-on experience with industry-leading fuzzers, and a passion for leveraging AI/LLM-based agentic frameworks to scale and automate vulnerability discovery.

Key Responsibilities

• Design, develop, and deploy AI-agent-driven fuzzing harnesses targeting Linux kernel subsystems, device drivers, and system interfaces using frameworks such as LangChain, Agno, AutoGen, or similar agentic orchestration tools.