AI Security Engineer Manager
San Juan, PR · On-site
Financials Cyber Security Cyber Security vigilantly protects Deloitte and client data. The team ... and Generative AI solutions. You will operate hands-on across high-visibility initiatives ...
AI Security Engineer Manager
San Juan, PR · On-site
Financials Cyber Security Cyber Security vigilantly protects Deloitte and client data. The team ... and Generative AI solutions. You will operate hands-on across high-visibility initiatives ...
AI Security Engineer Senior Manager
San Juan, PR · On-site
$112K - $153K/yr
... Generative AI systems at scale. You will operate at the intersection of cybersecurity, engineering, and innovation-ensuring AI capabilities are deployed securely, responsibly, and in alignment with ...
AI Security Engineer Senior Manager
San Juan, PR · On-site
$112K - $153K/yr
... Generative AI systems at scale. You will operate at the intersection of cybersecurity, engineering, and innovation-ensuring AI capabilities are deployed securely, responsibly, and in alignment with ...
Generative Ai Cybersecurity information
What is the difference between Generative Ai Cybersecurity vs Cybersecurity Analyst?
| Aspect | Generative Ai Cybersecurity | Cybersecurity Analyst |
|---|---|---|
| Required Credentials | Certifications in AI, cybersecurity, and data science (e.g., CISSP, CEH, AI certifications) | Certifications like CISSP, CompTIA Security+, CEH |
| Work Environment | Focus on developing AI models, threat detection algorithms, and automation tools | Monitoring security systems, analyzing threats, implementing security measures |
| Employer & Industry Usage | Tech companies, cybersecurity firms, organizations deploying AI-driven security solutions | All 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.
What is a $900000 AI job?
A $900,000 AI job typically refers to a high-level position in artificial intelligence, such as a senior AI researcher, machine learning director, or AI cybersecurity specialist, often requiring advanced skills, extensive experience, and relevant certifications. In the context of generative AI cybersecurity, such roles may involve developing secure AI systems, threat detection, and protecting AI infrastructure, with compensation reflecting expertise and responsibility.
Can you make $500,000 a year in cyber security?
Generative AI cybersecurity professionals with advanced skills, certifications, and extensive experience can potentially earn $500,000 or more annually, especially in senior or specialized roles such as security architects or consultants. Achieving this level often requires expertise in AI tools, threat analysis, and leadership in high-demand environments. Compensation varies based on industry, location, and individual qualifications.
How much does generative AI cybersecurity pay?
Generative AI cybersecurity professionals typically earn between $80,000 and $150,000 annually, depending on experience, location, and certifications. Senior roles or those with specialized skills in AI models and security tools can command higher salaries, especially in high-demand markets.
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 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.
Can generative AI be used in cyber security?
Generative AI is increasingly used in cybersecurity roles to identify vulnerabilities, generate realistic attack simulations, and develop adaptive defense mechanisms. Cybersecurity professionals leverage tools like machine learning models to enhance threat detection and automate response strategies, often requiring knowledge of AI algorithms and security protocols.
What are popular job titles related to Generative Ai Cybersecurity jobs in Puerto Rico? For Generative Ai Cybersecurity jobs in Puerto Rico, the most frequently searched job titles are:
What job categories do people searching Generative Ai Cybersecurity jobs in Puerto Rico look for? The top searched job categories for Generative Ai Cybersecurity jobs in Puerto Rico are:
What cities in Puerto Rico are hiring for Generative Ai Cybersecurity jobs? Cities in Puerto Rico with the most Generative Ai Cybersecurity job openings:
Deloitte rating
8.1
Based on 91 frontline employees who took The Breakroom Quiz
58th of 150 rated financial services
Job description
As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.
Recruiting for this role ends on 7/23/2026.
Work you'll do
You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.
Key Responsibilities
Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.
Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.
AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.
Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.
Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.
Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.
Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.
Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.
Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.
Impact
This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.
The successful candidate would possess these skills
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to mentor and provide clear guidance to others
The team
Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.
The ~3,000 professionals in DT - US deliver services including:
- Cyber Security
- Technology Support
- Technology & Infrastructure
- Applications
- Relationship Management
- Strategy & Communications
- Project Management
- Financials
Cyber Security
Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.
Areas of focus include:
- Risk & Compliance
- Identity & Access Management
- Data Protection
- Cyber Design
- Incident Response
- Security Architecture
- Business Partnership
Qualifications
Required:
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
- Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
- Minimum 1 year of people and/or process management experience
Preferred:
- Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
- Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
- Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
- Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
- Knowledge of data protection, identity/access management, and secure architecture patterns
- Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
- Strong communication skills with the ability to translate technical concepts into business-relevant insights
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. At Deloitte, it is not typical for an individual to be hired at or near the top of the range for their role and compensation decisions are dependent on the facts and circumstances of each case. A reasonable estimate of the current range is $118,700 to $243,700.
You may also be eligible to participate in a discretionary annual incentive program, subject to the rules governing the program, whereby an award, if any, depends on various factors, including, without limitation, individual and organizational performance.
EA_ExpHire
RITM10427821
As a Manager in AI Security Engineering, you will play a critical role in securing the development and deployment of AI/ML and Generative AI solutions. You will operate hands-on across high-visibility initiatives, embedding security, trust, and resilience into AI systems while enabling rapid, responsible innovation.
Recruiting for this role ends on 7/23/2026.
Work you'll do
You will bring strong engineering depth and applied AI knowledge, combined with expertise in cybersecurity principles, to design and deliver secure, scalable solutions. This role requires a collaborative, execution-focused leader who can influence teams, mentor engineers, and ensure AI systems meet enterprise security, risk, and compliance expectations.
Key Responsibilities
Secure, Outcome-Driven Delivery
Design and deliver AI-enabled solutions that are secure by design, balancing business value with risk mitigation. Solve complex problems while ensuring protection of data, models, and systems.
Hands-On AI Security Engineering
Actively contribute to architecture, design, and development of AI/ML and GenAI systems with embedded security controls. Integrate security across the SSDLC, including code reviews, testing, and deployment. In this role you will be responsible for managing AI defensive technologies and the operations of those technologies which will evolve over time.
AI Risk Identification and Mitigation
Identify and address AI-specific vulnerabilities, including prompt injection, data leakage, model manipulation, and misuse. Implement practical safeguards to ensure system integrity and trustworthiness.
Technical Leadership and Advocacy
Serve as a trusted technical voice for secure AI engineering. Ensure solutions are feasible, secure, and aligned with business and customer objectives.
Engineering Excellence with Security Focus
Maintain high standards for code quality, scalability, and security. Contribute to secure coding practices, reusable patterns, and continuous improvement across engineering teams.
Iterative and Responsible Innovation
Support rapid experimentation while applying appropriate security guardrails. Enable teams to innovate safely through controlled, risk-aware development practices.
Cross-Functional Collaboration
Partner closely with product, engineering, cybersecurity, and risk teams to embed AI security into solutions. Balance usability, performance, and security in decision-making.
Standards and Best Practices
Apply and help evolve standards for AI security, including data protection, access control, model validation, and monitoring within DevSecOps and MLOps pipelines.
Communication and Influence
Clearly articulate technical risks, trade-offs, and solutions to both technical and non-technical stakeholders. Contribute to alignment and informed decision-making.
Impact
This role directly contributes to reducing enterprise risk and strengthening trust in AI systems. Your work will enable secure adoption of AI capabilities while protecting critical assets and maintaining compliance.
The successful candidate would possess these skills
- Ability to work independently and collaborate as part of a team
- Effective written and verbal communication skills
- Meticulous attention to detail and quality of work product
- Ability to build and sustain professional relationships
- Ability to lead projects or workstreams
- Ability to manage and prioritize multiple tasks in a fast-paced and dynamic environment
- Strong interpersonal skills and professional demeanor
- Ability to meet deadlines
- Ability to mentor and provide clear guidance to others
The team
Deloitte Technology US (DT - US) helps power Deloitte's success, which serves many of the world's largest, most respected organizations. We develop and deploy cutting-edge internal and go-to-market solutions that help Deloitte operate effectively and lead in the market. Our reputation is built on a tradition of delivering with excellence.
The ~3,000 professionals in DT - US deliver services including:
- Cyber Security
- Technology Support
- Technology & Infrastructure
- Applications
- Relationship Management
- Strategy & Communications
- Project Management
- Financials
Cyber Security
Cyber Security vigilantly protects Deloitte and client data. The team leads a strategic cyber risk program that adapts to a rapidly changing threat landscape, changes in business strategies, risks, and vulnerabilities. Using situational awareness, threat intelligence, and building a security culture across the organization, the team helps to protect the Deloitte brand.
Areas of focus include:
- Risk & Compliance
- Identity & Access Management
- Data Protection
- Cyber Design
- Incident Response
- Security Architecture
- Business Partnership
Qualifications
Required:
- Bachelor's degree or equivalent in Computer Science, Computer Engineering, Business Administration
- Minimum 6 years of relevant experience in software engineering, cybersecurity, and/or including AI/ML, with hands-on delivery experience
- Minimum 1 year of people and/or process management experience
Preferred:
- Strong understanding of AI/GenAI technologies and associated security risks (e.g., prompt injection, data exposure, adversarial threats)
- Experience building and securing applications using Python, JavaScript, or similar, along with ML frameworks (e.g., PyTorch, TensorFlow)
- Familiarity with secure development practices (DevSecOps) and integrating security into CI/CD and MLOps pipelines
- Experience with cloud platforms (AWS, Azure, GCP) and cloud-native security principles
- Knowledge of data protection, identity/access management, and secure architecture patterns
- Ability to work across teams, mentor engineers, and contribute to a strong engineering culture
- Strong communication skills with the ability to translate technical concepts into business-relevant insights
The wage range for this role takes into account the wide range of factors that are considered in making compensation decisions including but not limited to skill sets; experience and training; licensure and certifications; and other business and organizational needs. The disclosed range estimate has not been adjusted for the applicable geographic differential associated with the location at which the position may be filled. A...