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Generative Ai Cybersecurity Jobs in Texas (NOW HIRING)

Celer Soft LLC

Cybersecurity Engineer

Dallas, TX · On-site

Job Title: Cybersecurity Engineer Role: AI Cloud Security Engineer Dallas TX (Hybrid) Position ... Generative AI and Agentic AI workloads hosted on AWS, with an emphasis on AWS Bedrock Security ...

New

HITRUST Service Corp.

AI Security Principal

Frisco, TX · On-site

... generative AI, machine learning technologies, AI-enabled software architectures, and information technology security. * Strong understanding of information security, cybersecurity risk management ...

HITRUST Services LLC

AI Security Principal

Frisco, TX · On-site

... generative AI, machine learning technologies, AI-enabled software architectures, and information technology security. * Strong understanding of information security, cybersecurity risk management ...

Visa

Cybersecurity Engineer

Austin, TX · On-site

As a member of Visa's Cybersecurity Engineering organization, the Analyst / Team Lead contributes ... Leverage Generative AI (GenAI) tooling and automation to reduce manual effort in security ...

Visa

Cybersecurity Engineer

Austin, TX · On-site

As a member of Visa's Cybersecurity Engineering organization, the Analyst / Team Lead contributes ... Leverage Generative AI (GenAI) tooling and automation to reduce manual effort in security ...

Northern Base

Gen AI Assessment Specialist

Irving, TX · On-site

... Cybersecurity, Information Security, AI Security, or Enterprise Security Assessment ✔ Strong experience in Generative AI (GenAI) security assessments, threat modeling, and AI risk analysis ✔ ...

Blue Cross of Idaho

AI Technical Lead

Meridian, TX · On-site +1

Develop and deploy machine learning and generative AI solutions that support enterprise use cases ... Bachelor or International Equivalency degree in Cybersecurity, Computer Science, Electrical ...

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Generative Ai Cybersecurity information

What is generative AI cybersecurity?

Generative AI Cybersecurity refers to the use of advanced artificial intelligence models, such as generative adversarial networks (GANs) and large language models, to enhance cybersecurity measures. These AI systems can identify vulnerabilities, simulate cyberattacks, generate realistic phishing attempts for training, and automate threat detection and response. The goal is to proactively strengthen defenses and adapt to evolving cyber threats by leveraging the creative and predictive capabilities of generative AI. This field is rapidly evolving as organizations seek to stay ahead of increasingly sophisticated cyber adversaries.

How does a generative AI cybersecurity professional typically collaborate with other teams in an organization?

A Generative AI Cybersecurity professional often works closely with data scientists, software engineers, and IT security teams to identify system vulnerabilities and design AI-driven defenses. Collaboration is essential when developing and deploying AI models that detect threats, as cross-team input ensures that solutions are both technically robust and aligned with organizational security policies. Regular meetings and knowledge-sharing sessions are common, helping to address emerging risks quickly and effectively. This collaborative environment not only strengthens security posture but also offers opportunities for learning and professional growth.

What are the key skills and qualifications needed to thrive as a generative AI cybersecurity specialist, and why are they important?

To thrive as a Generative AI Cybersecurity Specialist, you need a strong background in cybersecurity principles, AI/ML concepts, and programming (often with degrees in computer science or related fields). Familiarity with cybersecurity tools (like SIEM, IDS/IPS), knowledge of AI frameworks (such as TensorFlow or PyTorch), and relevant certifications (e.g., CISSP, CEH, or AI-specific credentials) are typically required. Analytical thinking, problem-solving, and effective communication are essential soft skills for identifying threats and collaborating across technical teams. These skills and qualifications are critical to protect advanced AI systems from evolving cyber threats and ensure secure deployment of generative AI technologies.

What is the difference between Generative Ai Cybersecurity vs Cybersecurity Analyst?

AspectGenerative Ai CybersecurityCybersecurity Analyst
Required CredentialsCertifications in AI, cybersecurity, and data science (e.g., CISSP, CEH, AI certifications)Certifications like CISSP, CompTIA Security+, CEH
Work EnvironmentFocus on developing AI models, threat detection algorithms, and automation toolsMonitoring security systems, analyzing threats, implementing security measures
Employer & Industry UsageTech companies, cybersecurity firms, organizations deploying AI-driven security solutionsAll industries, including finance, healthcare, government, and private sectors

While Generative Ai Cybersecurity involves creating AI models to enhance security, Cybersecurity Analysts focus on monitoring and responding to threats. Both roles require cybersecurity knowledge, but Generative Ai Cybersecurity emphasizes AI development and automation, whereas Cybersecurity Analysts concentrate on threat analysis and incident response.

Can generative AI be used in cybersecurity?

Generative AI is increasingly used in cybersecurity roles to develop advanced threat detection, automate incident response, and identify vulnerabilities. Cybersecurity professionals leverage tools like machine learning models to analyze large data sets and improve security measures efficiently.

What are popular job titles related to Generative Ai Cybersecurity jobs in Texas?

For Generative Ai Cybersecurity jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Generative Ai Cybersecurity jobs in Texas look for?

The top searched job categories for Generative Ai Cybersecurity jobs in Texas are:

What cities in Texas are hiring for Generative Ai Cybersecurity jobs?

Cities in Texas with the most Generative Ai Cybersecurity job openings:

Generative Ai Cybersecurity jobs near you
Infographic showing various Generative Ai Cybersecurity job openings in Texas as of August 2026, with employment types broken down into 80% Full Time, 18% Part Time, and 2% Contract. Highlights an 63% Physical, 4% Hybrid, and 33% Remote job distribution.

Cybersecurity Engineer

Celer Soft LLC

Dallas, TX • On-site

Other

Posted 2 days ago

New

Job description

Job Title: Cybersecurity Engineer
Role: AI Cloud Security Engineer
Dallas TX (Hybrid)


Position Overview
The AI Cloud Security Engineer will implement and operationalize enterprise security capabilities across Airlines' cloud-hosted AI platforms. This role is primarily responsible for establishing preventive, detective, and governance controls for Generative AI and Agentic AI workloads hosted on AWS, with an emphasis on AWS Bedrock Security Guardrails, CrowdStrike AIDR for Agents, and frontier model security.
The ideal candidate bridges architecture design and hands-on automation, integrating frameworks such as NIST AI RMF, OWASP Top 10 for LLM Applications, and MITRE ATLAS into enterprise CI/CD pipelines and cloud security operating models.
Required Skills & Experience (Prioritized)
AWS AI & Bedrock Security (5+ years Cloud, 1-2+ years AI Security): Direct hands-on experience configuring AWS Bedrock Guardrails, model access policies, content moderation filters, and foundation model protections.
AWS Cloud Engineering & IaC: Strong proficiency with AWS core security (IAM, SCPs, AWS Organizations) and Infrastructure as Code (Terraform or CloudFormation).
Runtime Protection & EDR/AIDR: Proven experience deploying and managing CrowdStrike Falcon, CrowdStrike AIDR, or equivalent cloud runtime detection platforms.
GenAI / LLM / Agentic AI Security: Deep technical understanding of RAG architectures, AI agent frameworks, prompt injection mitigations, output validation, and token abuse prevention.
AI Vulnerability Testing: Practical experience conducting security assessments and penetration tests specific to LLMs, tool integrations, and data leakage scenarios.
CI/CD & DevSecOps: Experience integrating automated security gates and policy-as-code into continuous integration/continuous deployment pipelines.
Cloud Logging & Observability: Expertise in aggregating AI telemetry via Amazon CloudWatch, SIEM tools, or OpenTelemetry.
Qualifications & Education
Education: Bachelor s degree in Cybersecurity, Computer Science, Information Systems, Data Science, Engineering, or equivalent practical experience. Advanced degree preferred.
Basic Requirements: Must be at least 18 years old with legal authorization to work in the United States without sponsorship (Immigration Reform Act of 1986).
Preferred Certifications
AWS Certified Security - Specialty
AWS Certified AI Practitioner or AWS Cloud Practitioner
CrowdStrike Falcon Platform Certifications (e.g., CCFA, CCFR)
Industry Security Certifications: CISSP, CCSP, or GIAC Cloud Security (GCSA/GPCS)

Regards,

Ram

Celersoft LLC

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