Note: The job is a remote job and is open to candidates in USA. PineQ Lab Technology is seeking an experienced AI Information Security Engineer to secure AI and LLM applications across enterprise environments. The role focuses on designing AI security controls and guardrails, mitigating AI-specific threats, protecting data, and supporting AI governance, monitoring, compliance, and incident response.
Responsibilities
- Design and implement AI/LLM security controls and guardrails
- Identify and mitigate AI-specific threats including prompt injection, data leakage, model abuse, jailbreaks, and unauthorized access
- Develop prompt security and validation controls for enterprise AI applications
- Implement data security and privacy controls for LLM inputs, outputs, training data, and AI integrations
- Establish policies for secure use of LLMs, AI agents, APIs, and third-party AI platforms
- Perform AI security assessments, threat modeling, risk analysis, and vulnerability testing
- Monitor AI applications for security risks, anomalous behavior, and policy violations
- Collaborate with AI/ML, engineering, cloud, privacy, and cybersecurity teams to embed security into the AI development lifecycle
- Support AI governance, compliance, logging, monitoring, and incident response processes
Skills
- 5+ years of experience in Cybersecurity / Information Security , with hands-on AI/GenAI security experience
- Strong understanding of LLMs, Generative AI, AI Agents, prompt engineering, and AI architectures
- Experience with AI threat controls, prompt injection, jailbreaks, data leakage, and model security
- Strong knowledge of AI guardrails, content filtering, data loss prevention, and access controls
- Experience with OWASP Top 10 for LLM Applications and AI threat modeling
- Knowledge of cloud security, APIs, IAM, encryption, logging, and security monitoring
- Experience developing security policies and controls for enterprise AI/LLM platforms
- Experience with Microsoft Azure AI, AWS Bedrock, Google Vertex AI, OpenAI, or similar platforms
- Knowledge of NIST AI Risk Management Framework (AI RMF) and responsible AI practices
- Experience with AI security/guardrail tools and platforms
- Familiarity with RAG, vector databases, MCP, AI agents, and LLM gateways
- Security certifications such as CISSP, CCSP, or GIAC are a plus
Benefits
- USA – Remote
- 12+ Months, Extendable project
Company Overview