AI Solution Security Engineer
Job Description
This role focuses on architecting AI security systems and validation frameworks for agentic platforms, with emphasis on prompt injection resilience, access protection, and vulnerability auto-mitigation. You will also serve as a key technical conduit between local engineering and central security teams to keep global alignment.
Role Overview
Within gTech Risk, you will help protect Google and its users by identifying and implementing controls for significant risks. In the AI Security function, you will act as core experts for the Functional Engineering pod (Strategy and Design), owning system design for autonomous risk identification, AI guardrails, and vulnerability auto-mitigation.
Responsibilities
- Design security architecture and validation frameworks for agentic platforms, including prompt injection resilience and data flow constraints.
- Create technical standards and automated workflows for vulnerability auto-mitigation, aligned with global SLO timelines.
- Architect automated access control systems, integration templates, and data flow constraints to prevent access abuse and data exfiltration.
- Develop holistic mapping of agentic threat models and engineering solutions to prevent and detect material risks before they manifest.
- Ensure technical architectures align with central security design standards and serve as the primary design conduit to central infrastructure.
- Provide precise technical designs for the Operational Engineering (Build) team to support software fulfillment.
Required Qualifications
- Bachelor's degree in Computer Science, Cybersecurity, a related technical field, or equivalent practical experience.
- 2+ years of experience in security engineering, threat modeling, systems design, or security architecture.
- Experience coding in C++, Java, Go, or Python.
Preferred Qualifications
- Master's degree or PhD in Computer Science or a related technical field.
- Experience designing security controls for large-scale distributed systems or cloud infrastructure.
- Experience architecting enterprise-scale security tools, access control systems, or observability platforms.
- Deep technical understanding of LLMs and AI security risks such as prompt injection and data poisoning, including deployment of deterministic security harnesses.
- Strong capability to influence executive engineering partners on critical design decisions.
Technologies
- C++
- Java
- Go
- Python
- Large Language Models (LLMs)
Compensation and Location
- Location: Chicago, IL (onsite)
- Salary: USD 147,000 - 210,000 per year
Benefits
- 15% bonus target
- Equity
- Benefits
- Health insurance