Staff AI Secuirty Researcher - Sentinellabs

Conduct advanced research to identify vulnerabilities within AI (LLMs, SLMs) models, agentic systems and their infrastructure, including prompt injection, jailbreaking, data exfiltration, and misuse vectors. Build threat models for emerging AI capabilities and deployment surfaces (agents, tool use, multimodal systems). Innovate and design novel methodologies and automated tools to systematically and continuously probe AI security mechanisms at scale. Partner with engineering and product teams to translate research findings into our Agentic Detection and Response offering. Stay informed on the latest academic, industry and threat landscape trends on adversarial ML, agentic and AI security. Mentor other researchers and engineers and help grow the team's technical capabilities. Publish research findings internally and externally through papers, blog posts, or industry conferences. 6+ years of experience in offensive research, red teaming or pentesting, with focus on AppSec or Identity. Hands-on experience with adversarial techniques against AI (LLMs, SLMs) and ML systems - prompt injection, jailbreaking, membership inference, model extraction, data poisoning, etc. Good understanding of identity/access management (IAM) protocols and tools. Familiarity with agentic attack taxonomies such as OWASP Top 10 for LLMs and MITRE ATLAS. Proficiency in programming and scripting languages (Python, JavaScript and Java) and Cloud environments (AWS, GCP, Azure, Kubernetes). Technical writing & content development skills. Publication record or demonstrable body of work in security research, adversarial ML, or AI safety (papers, disclosed vulnerabilities, open-source tools, etc.) - advantage. Experience in leading cross-functional technical initiatives - advantage. Restricted Stock Units (RSUs) Employee Stock Purchase Plan (ESPP) Competitive leave benefits Gender-neutral parental leave Employee Assistant Program Workout sessions and a Wellness App Medical and insurance benefits Pension Employee Assistance Program (EAP) Global home office allowance Mobile phone reimbursement Study Fund

Conduct advanced research to identify vulnerabilities within AI (LLMs, SLMs) models, agentic systems and their infrastructure, including prompt injection, jailbreaking, data exfiltration, and misuse vectors. Build threat models for emerging AI capabilities and deployment surfaces (agents, tool use, multimodal systems). Innovate and design novel methodologies and automated tools to systematically and continuously probe AI security mechanisms at scale. Partner with engineering and product teams to translate research findings into our Agentic Detection and Response offering. Stay informed on the latest academic, industry and threat landscape trends on adversarial ML, agentic and AI security. Mentor other researchers and engineers and help grow the team's technical capabilities. Publish research findings internally and externally through papers, blog posts, or industry conferences. 6+ years of experience in offensive research, red teaming or pentesting, with focus on AppSec or Identity. Hands-on experience with adversarial techniques against AI (LLMs, SLMs) and ML systems - prompt injection, jailbreaking, membership inference, model extraction, data poisoning, etc. Good understanding of identity/access management (IAM) protocols and tools. Familiarity with agentic attack taxonomies such as OWASP Top 10 for LLMs and MITRE ATLAS. Proficiency in programming and scripting languages (Python, JavaScript and Java) and Cloud environments (AWS, GCP, Azure, Kubernetes). Technical writing & content development skills. Publication record or demonstrable body of work in security research, adversarial ML, or AI safety (papers, disclosed vulnerabilities, open-source tools, etc.) - advantage. Experience in leading cross-functional technical initiatives - advantage. Restricted Stock Units (RSUs) Employee Stock Purchase Plan (ESPP) Competitive leave benefits Gender-neutral parental leave Employee Assistant Program Workout sessions and a Wellness App Medical and insurance benefits Pension Employee Assistance Program (EAP) Global home office allowance Mobile phone reimbursement Study Fund

Conduct advanced research to identify vulnerabilities within AI (LLMs, SLMs) models, agentic systems and their infrastructure, including prompt injection, jailbreaking, data exfiltration, and misuse vectors. Build threat models for emerging AI capabilities and deployment surfaces (agents, tool use, multimodal systems). Innovate and design novel methodologies and automated tools to systematically and continuously probe AI security mechanisms at scale. Partner with engineering and product teams to translate research findings into our Agentic Detection and Response offering. Stay informed on the latest academic, industry and threat landscape trends on adversarial ML, agentic and AI security. Mentor other researchers and engineers and help grow the team's technical capabilities. Publish research findings internally and externally through papers, blog posts, or industry conferences. 6+ years of experience in offensive research, red teaming or pentesting, with focus on AppSec or Identity. Hands-on experience with adversarial techniques against AI (LLMs, SLMs) and ML systems - prompt injection, jailbreaking, membership inference, model extraction, data poisoning, etc. Good understanding of identity/access management (IAM) protocols and tools. Familiarity with agentic attack taxonomies such as OWASP Top 10 for LLMs and MITRE ATLAS. Proficiency in programming and scripting languages (Python, JavaScript and Java) and Cloud environments (AWS, GCP, Azure, Kubernetes). Technical writing & content development skills. Publication record or demonstrable body of work in security research, adversarial ML, or AI safety (papers, disclosed vulnerabilities, open-source tools, etc.) - advantage. Experience in leading cross-functional technical initiatives - advantage. Restricted Stock Units (RSUs) Employee Stock Purchase Plan (ESPP) Competitive leave benefits Gender-neutral parental leave Employee Assistant Program Workout sessions and a Wellness App Medical and insurance benefits Pension Employee Assistance Program (EAP) Global home office allowance Mobile phone reimbursement Study Fund