Lead Security Engineer - AI Red Teaming Engineer

We are seeking a Lead Security Engineer - AI Red Teaming Engineer to focus on the behavioral and algorithmic safety of LLMs and Generative AI systems, ensuring they cannot be tricked into bypassing guardrails or leaking sensitive data.

Responsibilities

• Execute Direct and Indirect Prompt Injection attacks and jailbreaking techniques including multi-turn and roleplay scenarios to test LLM guardrails
• Identify vulnerabilities related to model behavior manipulation and potential data leakage
• Apply MITRE ATLAS and OWASP Top 10 for LLMs frameworks to structure adversarial testing methodologies
• Test Retrieval-Augmented Generation pipelines for data poisoning vulnerabilities
• Validate Agentic workflows against tool-use manipulation, goal hijacking and unauthorized permission escalation
• Develop and script custom boundary-testing payloads using Python
• Leverage AI red teaming and evaluation frameworks to assess model safety and resilience
• Document findings and provide remediation guidance to engineering teams
• Collaborate with cross-functional teams to strengthen defenses across AI systems

Requirements

• 5+ years of experience in adversarial AI testing including Direct and Indirect Prompt Injection, Jailbreaking and model behavior manipulation
• Familiarity with MITRE ATLAS, MITRE ATT&CK and OWASP Top 10 for LLMs frameworks
• Experience testing RAG pipelines for data poisoning and validating Agentic workflows against tool-use manipulation and goal hijacking
• Proficiency in AI red teaming tools such as PyRIT, GARAK and Giskard or enterprise suites like Confident AI or Repello
• Understanding of LLM fundamentals including tokens, embeddings and context windows
• Skills in Python programming for scripting custom boundary-testing payloads
• Knowledge of LLM security, Prompt Engineering and Security practices
• Background in Multi-Agent Systems Evaluation and Testing
• English proficiency at B2 level or higher

Nice to have

• Expertise in AI Solution Engineering
• Knowledge of Machine Learning