Job Description Senior Consultant AI Security
Position Title: Senior Consultant AI Security
Location: Flexible / Hybrid
Experience
815 years of experience in Cybersecurity, security architecture, or consulting ,with at least 23 years of experience in AI/ML Security, Cloud Security, or emerging technology security domains.
Role Summary
We are seeking an experienced
Senior Consultant AI Security to support the design, implementation, and operationalization of security capabilities for enterprise AI initiatives. This role requires a combination of strategic advisory expertise and hands-on technical capability to establish, deploy, and mature security controls across the AI lifecycle.
The successful candidate will work closely with business stakeholders, AI engineering teams, security operations, governance teams, and enterprise architects to ensure that AI platforms, models, and supporting infrastructure are secure, compliant, and resilient.
This role demands expertise in AI security frameworks, cloud security, governance, risk management, threat modelling, and security engineering for emerging AI technologies.
Key Responsibilities
Strategic & Advisory Responsibilities
- Provide strategic guidance on enterprise AI security architecture, governance, and risk management.
- Develop and implement AI security strategies, roadmaps, standards, and operating models.
- Define security controls and guardrails for AI/ML platforms, GenAI applications, and agentic AI systems.
- Conduct AI risk assessments and advise on secure adoption of AI technologies.
- Align AI security initiatives with organizational cybersecurity strategy, regulatory requirements, and industry best practices.
- Support the establishment of AI governance frameworks, policies, and control libraries.
- Collaborate with enterprise architects, legal, compliance, privacy, and risk teams.
Technical & Hands-on Responsibilities
- Design and implement security controls across the AI/ML lifecycle, including:
- Data ingestion and preprocessing
- Model training and validation
- Model deployment and inference
- Monitoring and model lifecycle management
- Perform threat modelling and security architecture reviews for AI systems and applications.
- Knowledge on AI-specific threats, including:
- Prompt injection attacks
- Data poisoning
- Model theft and extraction
- Adversarial attacks
- Supply chain attacks
- Model inversion and privacy leakage
- Jailbreaking attacks
- Participate in security assessments for AI environments.
- Develop security requirements for AI platforms hosted in cloud environments.
- Support implementation of secure MLOps and DevSecOps practices.
Operational Responsibilities
- Collaborate with SOC, Incident Response, Threat Intelligence, and Threat Hunting teams to establish AI threat detection capabilities.
- Define use cases, detection rules, and monitoring frameworks for AI-related threats.
- Support incident response investigations involving AI systems and models.
- Conduct security awareness and technical training sessions related to AI security.
Required Qualifications
- Bachelors degree in computer science, Cybersecurity, Information Security, or related field.
- Experience supporting enterprise AI, ML, or GenAI deployments.
- Strong understanding of:
- AI/ML architectures and workflows
- Generative AI and Large Language Models (LLMs)
- Cloud security architectures (AWS, Azure, GCP)
- Security architecture and threat modelling
- Identity and Access Management (IAM)
- Data security and privacy controls
- Secure software development lifecycle (SSDLC)
- Hands-on experience with security assessments and implementation of security controls.
Preferred Technical Skills
- AI Security frameworks and standards:
- OWASP Top 10 for LLM Applications
- NIST AI Risk Management Framework (AI RMF)
- MITRE ATLAS Framework
- Experience with:
- LLM security testing
- AI red teaming
- Model governance
- Secure MLOps platforms
- Container and Kubernetes security
- API security
- Data Loss Prevention (DLP)
- Security technologies:
- SIEM platforms
- EDR/XDR solutions
- CSPM/CNAPP tools
- Vulnerability management platforms
- Secrets management solutions
Preferred Certifications
- CISSP
- CCSP
- CISM
- GIAC certifications
- Cloud security certifications (AWS, Azure, GCP)
- AI Security certifications (if applicable)
- Security architecture certifications
Key Competencies
- Strategic thinking and advisory capability
- Strong stakeholder management
- Excellent communication and presentation skills
- Security architecture and engineering expertise
- Problem-solving and analytical mindset
- Ability to operate both strategically and hands-on
- Experience working in cross-functional enterprise environments
Success Criteria
The Successful Candidate Will
- Establish robust security controls for enterprise AI deployments.
- Implement practical AI security capabilities and operational processes.
- Enable secure adoption of GenAI and AI platforms.
- Improve organizational resilience against emerging AI threats.
- Build sustainable AI governance, monitoring, and security practices.
AI Automation, Strategic Planning
