Security Researcher

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.

We are currently seeking a dynamic Security Researcher/Pentester to contribute to the success of our rapidly growing business.

We are looking for a highly motivated individual who can thrive in a fast pace environment and successfully contribute to the team.

You would act as a Security Researcher/Penetration Tester.

This is a highly technical role, combining cutting-edge AI and LLM-powered attack techniques with traditional penetration testing skills.

You will assist the Information Security leadership on evaluating the security posture of Fortinet Cloud Services.

This position will be strongly focusing on AI powered red teaming, cloud security adversarial research and LLM exploitation.

As a Security Researcher/Pentester, your responsibilities will include:

• Conduct regularly penetration tests and security evaluations on Fortinet cloud products, covering web applications and server backend under various authentication level to identify vulnerabilities and security risks.
• Investigating and Writing POCs for published vulnerabilities and help production team to evaluating the exploitability and risks.
• Red team activities, specifically on developing AI-assisted scripts, agents, and programs to penetrate and infiltrate in-scope systems and ICT technologies; this includes leveraging LLMs as autonomous attack agents capable of chaining exploits across cloud environments.
• Collecting threat intelligence, evaluating and maintaining traditional Pentest tools, and tracking emerging AI/LLM-based offensive security techniques and tooling.
• Conduct AI red team exercises targeting LLM-integrated cloud services and AI APIs,including prompt injection, indirect prompt injection, jailbreaking, and model inversion attacks.
• Perform LLM fine-tuning and abliteration research — including training uncensored or capability-unlocked variants of open-source models (LLaMA, Gemma4) via LoRA/QLoRA and representation-engineering techniques
• Develop and operate LLM-powered penetration testing pipelines: using AI agents (ReAct, tool-use) to automate reconnaissance, vulnerability enumeration, exploit generation, and post-exploitation chaining against cloud-native targets (Kubernetes clusters, serverless functions, IAM privilege escalation paths, cloud storage misconfigurations).