AI Security Engineer

About the role

We are looking for an AI Security Engineer to design and implement security controls for AI systems, large language models (LLMs), and autonomous agents. You will protect these technologies from emerging threats such as prompt injection, jailbreaks, tool abuse, and data exfiltration while bridging traditional cybersecurity with AI‑specific practices.

Key responsibilities

• Design AI security architecture and conduct AI‑specific threat modeling.
• Implement defenses against prompt injection, jailbreaks, and agent tool abuse.
• Define identity, authentication, authorization, and access controls for AI workloads.
• Perform AI security testing, adversarial testing, and red‑team exercises.
• Conduct AI privacy reviews covering PII, prompts, outputs, and logs.
• Collaborate with AI Governance and Platform Engineering to strengthen overall security posture.
• Communicate AI‑specific risks and vulnerabilities to security leadership.
• Identify, remediate, and track emerging AI threats.
• Train delivery teams on AI security best practices and threat patterns.

Required profile

• 5+ years of cybersecurity or application security experience, including at least 2 years focused on AI/LLM/agent security.
• Strong knowledge of LLM and agent security threats such as prompt injection, jailbreaking, and data exfiltration.
• Solid foundation in IAM, network security, secure SDLC, and application security.
• Experience with AI/LLM security testing and adversarial testing tools.
• Excellent communication and stakeholder‑management skills.

Required skills

• AI/LLM security
• Identity and Access Management (IAM)
• Network security
• Secure Software Development Lifecycle (SDLC)
• Adversarial testing tools
• Azure AI Foundry Prompt Shields / content filtering
• AWS Bedrock Guardrails
• Google Vertex AI safety controls
• Open‑source tools such as NeMo Guardrails and Rebuff (a plus)
• AI privacy, data protection, and risk management