AI Security Engineer

Responsibilities

• Advise on and assess the security posture of AI/ML systems, including LLMs and GenAI pipelines
• Lead threat modeling exercises for AI workloads, covering prompt injection and data poisoning
• Guide secure integration of SaaS AI services and APIs like OpenAI and Azure OpenAI
• Evaluate controls for data ingestion pipelines, RAG architectures, and vector databases
• Serve as a security advisor to business stakeholders and AI/ML engineers
• Track emerging AI security research and adversarial techniques
• Produce security architecture documentation and risk assessments
• Develop training and awareness content regarding AI-specific risks

Requirements

• 5+ years of experience in security engineering (Cloud Security or AppSec)
• Hands-on experience securing Agentic AI solutions in an enterprise context
• Familiarity with AWS Bedrock, AWS SageMaker, Azure AI Foundry, or Google Vertex
• Proficiency in Python
• Solid understanding of LLMs, context engineering, and agentic tool usage
• Operational experience with Agentic Coding assistants like Claude Code, Cursor, or Codex
• Demonstrated experience in AI-specific threat modeling and data protection

Preferred Qualifications

• AWS Certified AI Practitioner or Machine Learning Engineer
• Azure AI Engineer Associate
• Claude Certified Architect
• Experience with model fine-tuning techniques
• Familiarity with red teaming agentic systems
• Experience with Policy as Code (Cedar, Rego) and IaC (Terraform, CloudFormation)
• Knowledge of MCP client/server architecture security risks

About the Company

GuidePoint Security is a rapidly growing, profitable, privately-held value added reseller that focuses exclusively on Information Security. Since 2011, GuidePoint has grown to over 1,200 employees, serving as a trusted advisor to more than 6,200 customers.