Join Fortinet, a cybersecurity pioneer with over two decades of excellence, as we continue to shape the future of cybersecurity and redefine the intersection of networking and security. At Fortinet, our mission is to safeguard people, devices, and data everywhere.
Fortinet is seeking an experienced and innovative Staff AI Security Engineer to join our Corporate Information Security team. As an AI Security Engineer, you will play a crucial role in ensuring the security, safety, and privacy of our AI-driven applications while collaborating with cross-functional teams and providing technical expertise.
Key Responsibilities:
- Serve as an AI security subject matter expert who provides guidance to internal teams
- Work closely with development teams, conduct code reviews, perform AI Red Teaming assessments, to identify vulnerabilities in existing codes and new features, and participate in architectural reviews to ensure security is considered early in the development lifecycle.
- Perform threat modeling for AI-related products, such as chatbots, MCPs implementations, and autonomous agents.
- Integrate Security and AI-Specific checks into CI/CD workflows to automate security testing and ensure consistent application of best practices.
- Develop, implement, and communicate vulnerability mitigation strategies
- Develop strategies, evaluate solutions, design and implement tools, processes and controls to ensure that security, safety and privacy are designed in Fortinet AI applications.
- Develop and maintain security guardrails, input/output filters, and policy enforcement layers for LLM interactions
- Proactively research new attack vectors on AI applications that may affect Fortinet applications and infrastructure.
- Be part of a global distributed team to share knowledge, workload and assignments. Strong sense of teamwork is required. Coach peers in AI/ML security concepts and best practices.
Minimum Qualifications
- 7+ years of work experience as an Information security, product security, application security, AI/ML or data science related fields.
- Strong understanding on LLM Based Application architectures, technologies, frameworks, and foundational concepts like training, vector databases, memory, tool usage, MCP, Agentic AI, Guardrails etc.
- Solid understanding on current attacks on ML models, including adversarial examples, prompt injection, training data extraction, model extraction, and data poisoning.
- Solid understanding on LLM moderation, prompt engineering and guardrails.
- Strong understanding on OWASP TOP 10 and OWASP LLM Top 10 risks.
- Strong understanding of common API security risks
- Strong understanding on Cloud-Native application architecture, microservices, containerization technologies, secure deployment and implementation issues.
- Proven experience in manual application penetration testing
- Proven experience in security code review
- Strong foundation in computer and network security, authentication & authorization, security protocols and applied cryptography
- Solid understanding on CI/CD pipelines, build systems and DevSecOps principles.
- Experience defining security architecture patterns and standards in a large enterprise organization.
- Experience with cloud-based security solutions and familiarity with cloud service providers, particularly in relation to AI Security
- Experience working with threat modeling methodologies such as STRIDE, MAESTRO etc.
- Solid understanding of OAuth and JWT implementations.
- Ability to organize & communicate effectively, both written and verbal, with technical and non-technical people across functional teams
- A BS degree in Computer Science, Cyber Security, other tech-related degree, or equivalent experience.
Ways to Stand Out
- MS or PhD in, Artificial Intelligence or related field
- Experience in AI Red teaming or adversarial testing of AI/ML applications.
- Use of AI in vulnerability research or some other offensive domain
- Experience analyzing AI-generated code for security issues
- Demonstrated experience in MLops or Deep learning related infrastructure
- Understanding of data science, statistical analysis, and visualization
- Background of AI Trust principles and familiarity with application of ethical and safety perspectives to AI implementations.
- Strong understanding on EU AI Act, GDPR, ISO 42001 or NIST AI RMF like frameworks.
This position is fully onsite and requires regular attendance at our Sunnyvale, CA location. Remote or hybrid arrangements are not available for this role.
About Our Team:
Join our team, known for its collaborative ethos, working seamlessly with global customers, internal engineering teams and product development groups. Our team culture emphasizes continuous learning, innovation, and a strong commitment to customer satisfaction. We embrace Fortinet’s core values of openness, teamwork and innovation, fostering an environment where team members support each other, share knowledge, and leverage AI to solve complex technical challenges. Our inclusive and dynamic team thrives on collaboration and is driven by the shared goal of maintaining Fortinet’s high standards of excellence in cybersecurity solutions.
Why Join Us:
We encourage candidates from all backgrounds and identities to apply. We offer a supportive work environment and a competitive Total Rewards package to support you with your overall health and financial well-being. Embark on a challenging, enjoyable, and rewarding career journey with Fortinet. Join us in bringing solutions that make a meaningful and lasting impact to our 660,000+ customers around the globe.
Must be authorized to work in the U.S. without sponsorship
The US base salary range for this full-time position is $170,000-$240,000. Fortinet offers employees a variety of benefits, including medical, dental, vision, life and disability insurance, 401(k), 11 paid holidays, vacation time, and sick time, as well as a comprehensive leave program.
Wage ranges are based on various factors, including the labour market, job type, and job level. Exact salary offers will be determined by factors such as the candidate's subject knowledge, skill level, qualifications, experience, and geographic location.
All roles are eligible to participate in the Fortinet equity program. Bonus eligibility is reviewed at the time of hire and annually at the Company’s discretion.
Skills Required
- 7+ years of experience in information security, product security, application security, AI/ML, or data science
- Strong understanding of LLM-based application architectures, technologies, frameworks, training, vector databases, memory, tool usage, MCP, agentic AI, and guardrails
- Understanding of attacks on ML models, including adversarial examples, prompt injection, training data extraction, model extraction, and data poisoning
- Understanding of LLM moderation, prompt engineering, and guardrails
- Understanding of OWASP Top 10 and OWASP LLM Top 10 risks
- Understanding of common API security risks
- Understanding of cloud-native architecture, microservices, containerization, secure deployment, and implementation issues
- Proven experience in manual application penetration testing
- Proven experience in security code review
- Foundation in computer and network security, authentication and authorization, security protocols, and applied cryptography
- Understanding of CI/CD pipelines, build systems, and DevSecOps principles
- Experience defining security architecture patterns and standards in a large enterprise organization
- Experience with cloud-based security solutions and cloud service providers, particularly for AI security
- Experience with threat modeling methodologies such as STRIDE and MAESTRO
- Understanding of OAuth and JWT implementations
- Effective written and verbal communication with technical and non-technical stakeholders
- Bachelor’s degree in Computer Science, Cybersecurity, another technology-related field, or equivalent experience
- Master’s or PhD in Artificial Intelligence or a related field
- Experience in AI red teaming or adversarial testing of AI/ML applications
- Experience using AI in vulnerability research or another offensive domain
- Experience analyzing AI-generated code for security issues
- Experience with MLOps or deep learning infrastructure
- Understanding of data science, statistical analysis, and visualization
- Understanding of AI trust principles and ethical and safety perspectives for AI implementations
- Understanding of the EU AI Act, GDPR, ISO 42001, or NIST AI RMF
Fortinet Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Fortinet and has not been reviewed or approved by Fortinet.
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Equity Value & Accessibility — Equity in the form of stock awards and RSUs is highlighted as a meaningful part of total compensation and one of the package’s strongest advantages. Recognition programs may include stock, further emphasizing equity’s role in rewards.
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Strong & Reliable Incentives — Performance bonuses and incentives are presented as key components of total rewards, with some roles achieving strong total compensation through these elements. Incentive opportunities are described as a major strength when included in an offer.
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Retirement Support — A 401(k) plan, often with matching contributions, and broader retirement and savings programs contribute to solid financial security. These elements are positioned as competitive features of the package.
Fortinet Insights
What We Do
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