How to Become an AI Security Engineer: Skills, Certifications, and Career Path

Organizations are racing to build AI into everything: customer service chatbots, coding assistants, search tools, and AI agents that can take action on their own. But every new AI system also creates new ways for attackers to cause harm. Someone has to make sure those systems are built and run securely.

That’s the job of an AI security engineer, one of the newest and fastest-growing roles in cybersecurity. This guide explains what AI security engineers do, how much they earn, the skills and certifications you need, and a step-by-step path to get there.

What Is an AI Security Engineer?

An AI security engineer protects artificial intelligence systems, including the models, the data they learn from, and the applications and agents built on top of them. The role sits at the intersection of cybersecurity and machine learning.

Traditional security engineers protect networks, servers, and applications. AI security engineers do that too, but they also defend against threats that only exist in AI systems, such as:

• Prompt injection, where attackers manipulate an AI model with crafted instructions
• Data poisoning, where attackers corrupt the data a model learns from
• Sensitive data leakage, where AI tools reveal confidential information
• Excessive agency, where AI agents have more permissions than they need
• Model theft and supply chain risks from third-party models and libraries

For a deeper look at these threats, read our guide to prompt injection, data poisoning, and the new AI attack surface.

Why AI Security Engineers Are in Demand

AI Adoption Is Outpacing Security

Many organizations are deploying AI tools faster than they can secure them. Security teams need specialists who understand how AI systems work and where they can fail.

Attackers Are Using AI Too

Criminals use AI to write convincing phishing messages, clone voices, and create deepfakes. Learn more in our guide to deepfakes, voice cloning, and AI-powered social engineering.

AI Agents Raise the Stakes

AI agents can browse the web, read files, send messages, and call other systems. If an attacker takes control of an agent, the damage can be real and immediate.

Regulations and Frameworks Are Growing

Organizations increasingly follow guidance like the NIST AI Risk Management Framework and the OWASP Top 10 for LLM Applications. They need professionals who can put those frameworks into practice. Learn more about cybersecurity compliance frameworks.

What Does an AI Security Engineer Do?

Day-to-day responsibilities vary by organization, but often include:

• Threat modeling AI systems to find where attacks could happen
• Securing AI applications and agents with access controls, input and output validation, and human approval for sensitive actions
• Testing AI systems through AI red teaming, including prompt injection and jailbreak attempts
• Protecting training and retrieval data from tampering and leakage
• Reviewing third-party models, datasets, and plugins for supply chain risks
• Securing cloud infrastructure that hosts AI models and data pipelines
• Monitoring AI systems for abuse, unusual behavior, and policy violations
• Writing AI security policies and guidance for developers and data scientists
• Working with engineering, data science, legal, and compliance teams to deploy AI responsibly

If you want a broader view of how AI is changing security work, read AI in cybersecurity: what CIAT students need to know.

AI Security Engineer Salary

AI security engineering is a specialized, high-demand role, and pay reflects that. According to ZipRecruiter, the average AI security engineer in the United States earns about $152,773 per year as of October 2026, with most salaries falling between $143,000 and $158,500. (ZipRecruiter)

For comparison, the average cybersecurity engineer earns about $136,847 per year, according to Salary.com.

Salary data in this post comes from Salary.com and ZipRecruiter. Salary.com does not yet track AI security engineer as a separate title.

Pay varies based on experience, location, industry, and the depth of your AI and security expertise.

Skills You Need to Become an AI Security Engineer

Cybersecurity Fundamentals

AI security builds on traditional security. You’ll need a solid grasp of:

• Network and cloud security
• Identity and access management and least privilege See our guide to IAM careers.
• Application security and secure coding
• Threat modeling and risk assessment
• Incident response and monitoring
• Encryption and data protection

AI and Machine Learning Knowledge

You don’t need to be a data scientist, but you do need to understand how AI systems are built and used:

• How machine learning models are trained and deployed. Start with What Is Machine Learning? and deep learning.
• How large language models (LLMs) work, including prompts, context, and fine-tuning
• How retrieval-augmented generation (RAG) connects AI to company data
• The difference between generative AI and predictive AI

Programming and Tools

• Python is the most important language for both AI and security automation. See why Python matters for AI and how to approach securing Python code.
• Familiarity with cloud platforms like AWS and Azure, where most AI workloads run. Explore cloud security tools.
• Understanding of DevSecOps practices for building security into development pipelines

AI Security Frameworks

• OWASP Top 10 for LLM Applications: The most critical security risks for AI applications
• MITRE ATLAS: A knowledge base of adversary tactics against AI systems
• NIST AI Risk Management Framework: Guidance for managing AI risk across an organization

Professional Skills

• Clear communication with developers, data scientists, and business leaders
• Curiosity and a habit of continuous learning, since the field changes quickly
• Creative, adversarial thinking to anticipate how AI systems could be misused

Certifications for AI Security Engineers

Because AI security is a new field, most professionals combine foundational security certifications with AI-focused credentials:

• CompTIA Security+: The essential foundation for cybersecurity roles. Certification · Bootcamp
• CompTIA SecAI+: Focuses specifically on securing AI systems and defending against AI-driven threats. Bootcamp · Read about CIAT’s SecAI+ certification training
• CompTIA PenTest+: Builds offensive testing skills that carry over to AI red teaming. Certification · Bootcamp
• CompTIA CySA+: Builds monitoring, detection, and response skills. Certification · Bootcamp
• Cloud security certifications: AWS Security Specialty and Azure Security Engineer cover securing the cloud platforms where AI runs.
• CISSP: Supports senior architecture and leadership roles. Certification · Bootcamp

CIAT’s Unlimited Certification Exam Retake Policy covers all CompTIA certifications, including Security+, SecAI+, PenTest+, and CySA+. The policy excludes CISSP and EC-Council CEH.

How to Become an AI Security Engineer: Step by Step

Step 1: Build an IT and Security Foundation

Start with networking, operating systems, and core security concepts. Certifications like CompTIA Network+ and Security+ give you a strong base. Not sure where to begin? See the best cybersecurity certifications for beginners.

Step 2: Gain Hands-On Security Experience

Most AI security engineers first work as security analysts, application security engineers, cloud security engineers, or penetration testers. Learn how to become a penetration tester or explore other paths in our guide to the top cybersecurity careers in the US.

Step 3: Learn Python and Cloud Skills

Python and cloud platforms are core to AI work. Practice writing scripts, automating tasks, and securing cloud resources.

Step 4: Learn How AI Systems Work

Take courses in machine learning and generative AI. Build small AI projects so you understand how models, prompts, and data pipelines fit together. You can also explore the broader path to becoming an AI engineer.

Step 5: Practice Attacking and Defending AI

Try prompt injection challenges, study the OWASP LLM Top 10, and experiment with securing your own AI projects. CTF competitions increasingly include AI-focused challenges.

Step 6: Earn AI Security Credentials

Once you have a security foundation, CompTIA SecAI+ validates your ability to secure AI systems and defend against AI-driven threats.

Step 7: Build a Portfolio and Apply

Document your AI security projects, write-ups, and lab work. Look for titles like AI security engineer, ML security engineer, LLM security engineer, AI red teamer, or application security engineer with an AI focus.

AI Security Engineer Career Path

AI security offers strong room for growth:

1. Security analyst or application security engineer: Builds core security skills
2. AI security engineer: Secures AI applications, models, and data
3. Senior AI security engineer or AI red team lead: Leads testing programs and complex projects
4. AI security architect: Designs AI security strategy across the organization
5. AI security manager or director: Leads teams and advises leadership on AI risk

AI security skills also connect to related roles, such as threat intelligence analysts tracking AI-driven threats and GRC professionals managing AI risk and compliance.

How CIAT Helps You Become an AI Security Engineer

• Cybersecurity programs with certifications built in: CIAT’s cybersecurity programs build the security foundation every AI security engineer needs, with industry certifications included in your coursework.
• AI and machine learning education: CIAT’s Certificate in AI and Machine Learning builds practical AI skills that pair well with a security background.
• The CompTIA SecAI+ Bootcamp: A 5-day, live online bootcamp focused on securing AI systems and defending against AI-driven threats.
• Hands-on practice: Hands-on lab kits and the Cybersecurity Club help you build real-world skills.
• Career support: CIAT Career Services helps with resumes, interview preparation, and job search strategy.

• Primary keyword: AI security engineer
• Secondary keywords: how to become an AI security engineer, AI security engineer salary, AI security certifications, AI security careers, AI red teaming, CompTIA SecAI+, LLM security
• Heading structure: H1 = post title. H2 = main sections. H3 = subsections and FAQ questions. No H4s.

Organizations are racing to build AI into everything: customer service chatbots, coding assistants, search tools, and AI agents that can take action on their own. But every new AI system also creates new ways for attackers to cause harm. Someone has to make sure those systems are built and run securely.

That’s the job of an AI security engineer, one of the newest and fastest-growing roles in cybersecurity. This guide explains what AI security engineers do, how much they earn, the skills and certifications you need, and a step-by-step path to get there.

What Is an AI Security Engineer?

An AI security engineer protects artificial intelligence systems, including the models, the data they learn from, and the applications and agents built on top of them. The role sits at the intersection of cybersecurity and machine learning.

Traditional security engineers protect networks, servers, and applications. AI security engineers do that too, but they also defend against threats that only exist in AI systems, such as:

• Prompt injection, where attackers manipulate an AI model with crafted instructions
• Data poisoning, where attackers corrupt the data a model learns from
• Sensitive data leakage, where AI tools reveal confidential information
• Excessive agency, where AI agents have more permissions than they need
• Model theft and supply chain risks from third-party models and libraries

For a deeper look at these threats, read our guide to prompt injection, data poisoning, and the new AI attack surface.

Why AI Security Engineers Are in Demand

AI Adoption Is Outpacing Security

Many organizations are deploying AI tools faster than they can secure them. Security teams need specialists who understand how AI systems work and where they can fail.

Attackers Are Using AI Too

Criminals use AI to write convincing phishing messages, clone voices, and create deepfakes. Learn more in our guide to deepfakes, voice cloning, and AI-powered social engineering.

AI Agents Raise the Stakes

AI agents can browse the web, read files, send messages, and call other systems. If an attacker takes control of an agent, the damage can be real and immediate.

Regulations and Frameworks Are Growing

Organizations increasingly follow guidance like the NIST AI Risk Management Framework and the OWASP Top 10 for LLM Applications. They need professionals who can put those frameworks into practice. Learn more about cybersecurity compliance frameworks.

What Does an AI Security Engineer Do?

Day-to-day responsibilities vary by organization, but often include:

• Threat modeling AI systems to find where attacks could happen
• Securing AI applications and agents with access controls, input and output validation, and human approval for sensitive actions
• Testing AI systems through AI red teaming, including prompt injection and jailbreak attempts
• Protecting training and retrieval data from tampering and leakage
• Reviewing third-party models, datasets, and plugins for supply chain risks
• Securing cloud infrastructure that hosts AI models and data pipelines
• Monitoring AI systems for abuse, unusual behavior, and policy violations
• Writing AI security policies and guidance for developers and data scientists
• Working with engineering, data science, legal, and compliance teams to deploy AI responsibly

If you want a broader view of how AI is changing security work, read AI in cybersecurity: what CIAT students need to know.

AI Security Engineer Salary

AI security engineering is a specialized, high-demand role, and pay reflects that. According to ZipRecruiter, the average AI security engineer in the United States earns about $152,773 per year as of October 2026, with most salaries falling between $143,000 and $158,500. (ZipRecruiter)

For comparison, the average cybersecurity engineer earns about $136,847 per year, according to Salary.com.

Salary data in this post comes from Salary.com and ZipRecruiter. Salary.com does not yet track AI security engineer as a separate title.

Pay varies based on experience, location, industry, and the depth of your AI and security expertise.

Skills You Need to Become an AI Security Engineer

Cybersecurity Fundamentals

AI security builds on traditional security. You’ll need a solid grasp of:

• Network and cloud security
• Identity and access management and least privilege See our guide to IAM careers.
• Application security and secure coding
• Threat modeling and risk assessment
• Incident response and monitoring
• Encryption and data protection

AI and Machine Learning Knowledge

You don’t need to be a data scientist, but you do need to understand how AI systems are built and used:

• How machine learning models are trained and deployed. Start with What Is Machine Learning? and deep learning.
• How large language models (LLMs) work, including prompts, context, and fine-tuning
• How retrieval-augmented generation (RAG) connects AI to company data
• The difference between generative AI and predictive AI

Programming and Tools

• Python is the most important language for both AI and security automation. See why Python matters for AI and how to approach securing Python code.
• Familiarity with cloud platforms like AWS and Azure, where most AI workloads run. Explore cloud security tools.
• Understanding of DevSecOps practices for building security into development pipelines

AI Security Frameworks

• OWASP Top 10 for LLM Applications: The most critical security risks for AI applications
• MITRE ATLAS: A knowledge base of adversary tactics against AI systems
• NIST AI Risk Management Framework: Guidance for managing AI risk across an organization

Professional Skills

• Clear communication with developers, data scientists, and business leaders
• Curiosity and a habit of continuous learning, since the field changes quickly
• Creative, adversarial thinking to anticipate how AI systems could be misused

Certifications for AI Security Engineers

Because AI security is a new field, most professionals combine foundational security certifications with AI-focused credentials:

• CompTIA Security+: The essential foundation for cybersecurity roles. Certification · Bootcamp
• CompTIA SecAI+: Focuses specifically on securing AI systems and defending against AI-driven threats. Bootcamp · Read about CIAT’s SecAI+ certification training
• CompTIA PenTest+: Builds offensive testing skills that carry over to AI red teaming. Certification · Bootcamp
• CompTIA CySA+: Builds monitoring, detection, and response skills. Certification · Bootcamp
• Cloud security certifications: AWS Security Specialty and Azure Security Engineer cover securing the cloud platforms where AI runs.
• CISSP: Supports senior architecture and leadership roles. Certification · Bootcamp

CIAT’s Unlimited Certification Exam Retake Policy covers all CompTIA certifications, including Security+, SecAI+, PenTest+, and CySA+. The policy excludes CISSP and EC-Council CEH.

How to Become an AI Security Engineer: Step by Step

Step 1: Build an IT and Security Foundation

Start with networking, operating systems, and core security concepts. Certifications like CompTIA Network+ and Security+ provide a strong foundation. Not sure where to begin? See the best cybersecurity certifications for beginners.

Step 2: Gain Hands-On Security Experience

Most AI security engineers first work as security analysts, application security engineers, cloud security engineers, or penetration testers. Learn how to become a penetration tester or explore other paths in our guide to the top cybersecurity careers in the US.

Step 3: Learn Python and Cloud Skills

Python and cloud platforms are core to AI work. Practice writing scripts, automating tasks, and securing cloud resources.

Step 4: Learn How AI Systems Work

Take courses in machine learning and generative AI. Build small AI projects so you understand how models, prompts, and data pipelines fit together. You can also explore the broader path to becoming an AI engineer.

Step 5: Practice Attacking and Defending AI

Try prompt injection challenges, study the OWASP LLM Top 10, and experiment with securing your own AI projects. CTF competitions increasingly include AI-focused challenges.

Step 6: Earn AI Security Credentials

Once you have a security foundation, CompTIA SecAI+ validates your ability to secure AI systems and defend against AI-driven threats.

Step 7: Build a Portfolio and Apply

Document your AI security projects, write-ups, and lab work. Look for titles like AI security engineer, ML security engineer, LLM security engineer, AI red teamer, or application security engineer with an AI focus.

AI Security Engineer Career Path

AI security offers strong room for growth:

1. Security analyst or application security engineer: Builds core security skills
2. AI security engineer: Secures AI applications, models, and data
3. Senior AI security engineer or AI red team lead: Leads testing programs and complex projects
4. AI security architect: Designs AI security strategy across the organization
5. AI security manager or director: Leads teams and advises leadership on AI risk

AI security skills also connect to related roles, such as threat intelligence analysts tracking AI-driven threats and GRC professionals managing AI risk and compliance.

How CIAT Helps You Become an AI Security Engineer

• Cybersecurity programs with certifications built in: CIAT’s cybersecurity programs build the security foundation every AI security engineer needs, with industry certifications included in your coursework.
• AI and machine learning education: CIAT’s Certificate in AI and Machine Learning builds practical AI skills that pair well with a security background.
• The CompTIA SecAI+ Bootcamp: A 5-day, live online bootcamp focused on securing AI systems and defending against AI-driven threats.
• Hands-on practice: Hands-on lab kits and the Cybersecurity Club help you build real-world skills.
• Career support: CIAT Career Services helps with resumes, interview preparation, and job search strategy.

Secure the AI Revolution: Start Your Path to AI Security Engineering

AI is changing how every organization works, and it’s changing how attackers operate too. AI security engineers make sure the models, data, and agents businesses depend on can’t be turned against them. It’s a new, fast-growing, and well-paid specialty, and the professionals who build these skills now will help shape how AI is secured for years to come.

The path starts with a strong cybersecurity foundation and grows with AI-focused skills. CIAT’s cybersecurity programs build the core security expertise employers expect, and the 5-day CompTIA SecAI+ Bootcamp helps experienced professionals specialize in securing AI systems and defending against AI-driven threats, backed by CIAT’s unlimited retake policy for CompTIA exams.

Ready to become the expert who secures AI?

Frequently Asked Questions About AI Security Engineers