About the role

Senior Software Dev QA Specialist leading the design of cybersecurity solutions at Fortinet. Focus on integrating diverse products and AI-driven threat detection.

Responsibilities

Design solutions for cybersecurity products, including WAF, Load Balancer, firewall, and more
Design integrated solutions using diverse cybersecurity products to combat a range of threats, including DDoS attacks, automated threats, sensitive data breaches, web attacks, and other advanced cyber threats
Research, evaluate, and design AI-powered threat detection solutions, including anomaly detection, behavioral analysis, and ML-driven attack classification
Analyze security risks associated with LLM and Generative AI applications, including prompt injection, model abuse, data leakage, and AI-specific API threats; design and validate corresponding protection strategies
Develop and optimize security solutions for cloud platforms and SaaS products
Research the latest developments in cybersecurity, conduct competitive analyses, and continuously incorporate new technologies, methodologies, and features — with a focus on emerging AI/ML-driven attack vectors and defense mechanisms — into product designs
Produce Product Requirement Documents (PRDs), write articles, and conduct knowledge-sharing sessions within the team

Strong background in cybersecurity technologies such as WAF, API Security, Bot Management, Load Balancing, Firewall, DDoS protection, or SaaS/cloud platform security
Solid understanding of network protocols, such as TCP/IP and HTTPS/SSL, as well as routing and switching technologies
Proficiency in scripting languages for tasks like data analysis, attack analysis, and security testing
Solid understanding of AI/ML concepts applied to cybersecurity, such as anomaly detection models, behavioral profiling, and AI-driven threat intelligence
Familiarity with LLM and Generative AI security risks, including but not limited to prompt injection, jailbreaking, model inversion, and sensitive data exposure through AI APIs
Experience evaluating or designing security controls for AI-powered applications and services (e.g., Retrieval-Augmented Generation pipelines, AI agents, LLM-integrated APIs) is a strong plus
Experience with virtualization and cloud-native security practices is a plus
Familiarity with web application vulnerabilities is an advantage, including the OWASP Top 10 and the OWASP Top 10 for LLM Applications
Knowledge of Machine Learning and Big Data analysis is an advantage
Strong written and verbal communication skills
Excellent problem-solving and troubleshooting abilities
Highly motivated, responsible, and a quick learner