Cybersecurity Engineer

Intone Inc; Dallas (TX); On-site; USD 117,000 - 172,000; Full time

Job summary

Intone Inc. in Dallas, Texas seeks a Cybersecurity Engineer for a 6-month contract to operationalize enterprise security across GenAI and Agentic AI workloads in cloud environments.

You will design, implement, and enforce guardrails, access policies, and detection for AI platforms and pipelines. The role requires hands-on experience with AWS Bedrock Guardrails, IAM, Terraform/CloudFormation, and CrowdStrike in cloud deployments, plus strong threat modeling and CI/CD security integration.

Qualifications

• 5+ years of cloud experience with 1–2+ years in AI security.
• Direct hands-on experience configuring AWS Bedrock Guardrails, model access policies, content moderation filters, and foundation model protections.
• Strong proficiency with AWS core security (IAM, SCPs, AWS Organizations) and Infrastructure as Code (Terraform or CloudFormation).
• Proven experience deploying and managing CrowdStrike Falcon, CrowdStrike AIDR, or equivalent cloud runtime detection platforms.
• Deep technical understanding of RAG architectures, AI agent frameworks, prompt injection mitigations, output validation, and token abuse prevention.
• Practical experience conducting security assessments and penetration tests specific to LLMs, tool integrations, and data leakage scenarios.
• Experience integrating automated security gates and policy-as-code into continuous integration/continuous deployment pipelines.
• Expertise in aggregating AI telemetry via Amazon CloudWatch, SIEM tools, or OpenTelemetry.
• Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Data Science, Engineering, or equivalent practical experience.
• Proven ability to translate complex AI cybersecurity risks into actionable roadmaps for engineering teams and senior leadership.
• Collaborative mindset with experience working in Agile, cross-functional delivery teams.
• Strong critical-thinking skills to analyze emerging AI threat vectors and quickly adapt defense controls.

Responsibilities

• Design, configure, and maintain security controls for GenAI and Agentic AI solutions in AWS, including AWS Bedrock Guardrails, content filtering, sensitive information redaction, token protection, and model access controls.
• Implement and operationalize runtime protection and detection for foundation models, agents, and cloud workloads.
• Develop and execute adversarial security tests targeting LLMs and AI agents, including prompt injection, jailbreaking, tool abuse, and data exfiltration scenarios.
• Partner with platform and engineering teams to deploy guardrails-as-code using Terraform or CloudFormation, embedding automated AI security checks into deployment pipelines.
• Configure logging, telemetry, and monitoring across AI services to pipe alerts into enterprise SOC platforms.
• Conduct threat modeling and security reviews for RAG architectures, agent orchestration frameworks, and tool integrations aligned with NIST AI RMF and MITRE ATLAS.

Skills

Cloud security

AI security

Guardrails-as-code

Terraform

CloudFormation

Penetration testing

Threat modeling

IAM management

SIEM

RAG architectures

OpenTelemetry

Education

Bachelor's degree

Tools

AWS Bedrock Guardrails

CloudFormation

Terraform

CrowdStrike Falcon

CrowdStrike AIDR

OpenTelemetry

Amazon CloudWatch

IAM

AWS Organizations

Job description

This is a 6-month contract position for a Cybersecurity Engineer located in Dallas, Texas. You will implement and operationalize enterprise security capabilities across cloud-hosted AI platforms, with a focus on establishing preventive, detective, and governance controls for Generative AI and Agentic AI workloads. This role bridges architecture design and hands-on automation, integrating security frameworks into enterprise CI/CD pipelines and cloud security operating models.

Responsibilities

• Design, configure, and maintain security controls for GenAI and Agentic AI solutions in AWS, including AWS Bedrock Guardrails, content filtering, sensitive information redaction, token protection, and model access controls.
• Implement and operationalize runtime protection and detection for foundation models, agents, and cloud workloads.
• Develop and execute adversarial security tests targeting LLMs and AI agents, including prompt injection, jailbreaking, tool abuse, and data exfiltration scenarios.
• Partner with platform and engineering teams to deploy guardrails-as-code using Terraform or CloudFormation, embedding automated AI security checks into deployment pipelines.
• Configure logging, telemetry, and monitoring across AI services to pipe alerts into enterprise SOC platforms.
• Conduct threat modeling and security reviews for RAG architectures, agent orchestration frameworks, and tool integrations aligned with NIST AI RMF and MITRE ATLAS.

Qualifications

• Required

  • 5+ years of cloud experience with 1–2+ years in AI security.
  • Direct hands-on experience configuring AWS Bedrock Guardrails, model access policies, content moderation filters, and foundation model protections.
  • Strong proficiency with AWS core security (IAM, SCPs, AWS Organizations) and Infrastructure as Code (Terraform or CloudFormation).
  • Proven experience deploying and managing CrowdStrike Falcon, CrowdStrike AIDR, or equivalent cloud runtime detection platforms.
  • Deep technical understanding of RAG architectures, AI agent frameworks, prompt injection mitigations, output validation, and token abuse prevention.
  • Practical experience conducting security assessments and penetration tests specific to LLMs, tool integrations, and data leakage scenarios.
  • Experience integrating automated security gates and policy-as-code into continuous integration/continuous deployment pipelines.
  • Expertise in aggregating AI telemetry via Amazon CloudWatch, SIEM tools, or OpenTelemetry.
  • Bachelor's degree in Cybersecurity, Computer Science, Information Systems, Data Science, Engineering, or equivalent practical experience.
  • Proven ability to translate complex AI cybersecurity risks into actionable roadmaps for engineering teams and senior leadership.
  • Collaborative mindset with experience working in Agile, cross-functional delivery teams.
  • Strong critical-thinking skills to analyze emerging AI threat vectors and quickly adapt defense controls.

• Preferred

  • Advanced degree in a relevant field.
  • AWS Certified Security – Specialty.
  • AWS Certified AI Practitioner or AWS Cloud Practitioner.
  • CrowdStrike Falcon Platform Certifications (e.g., CCFA, CCFR).
  • CISSP, CCSP, or GIAC Cloud Security (GCSA/GPCS).