AI Information Security Engineer

PineQ Lab Technology; United States; On-site; USD 120,000 - 180,000; Full time

Job summary

PineQ Lab Technology is seeking an experienced AI Information Security Engineer to design and implement security controls for AI/LLM applications across enterprise environments.

The role focuses on AI threat detection, prompt security, data protection, guardrails, and secure AI adoption, with collaboration across AI/ML, engineering, cloud, privacy, and cybersecurity teams.

Qualifications

• 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.

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

Cybersecurity

AI/GenAI security

Threat modeling

Cloud security

IAM & encryption

AI guardrails

Tools

Azure AI

AWS Bedrock

Google Vertex AI

OpenAI

Job description

We are looking for an experienced AI Information Security Engineer to design and implement security controls for AI/LLM applications. The role will focus on AI threat detection, prompt security, data protection, guardrails, and secure AI adoption across enterprise environments.

Key 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.

Required 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.

Preferred Skills

• 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.

AI Security | AI Infosec | GenAI Security | LLM Security | AI Threat Controls | Prompt Security | Prompt Injection | AI Guardrails | Data Security | Data Leakage Prevention | AI Governance | OWASP LLM | AI Risk Management | Cloud Security