Internship in Cybersecurity at Mapfre, gaining hands - on experience in incident response and data analysis. Working within a collaborative team to develop cybersecurity skills and knowledge.
About the role
- AI Security Architect designing and governing security frameworks for AI; partnering with engineering teams to ensure secure development and compliance. Influencing organizational policy and risk posture in cybersecurity.
Responsibilities
- Develop secure-by-design architecture guidelines for AI/ML platforms, including data ingestion, model training, model deployment, and inference layers.
- Define reference security architectures, patterns, and guardrails that enable secure AI development while minimizing manual review and approval friction.
- Partner with respective engineering teams to automate / bake in the security guardrails where possible.
- Design risk-based, proportionate AI security controls that satisfy regulatory and enterprise requirements while enabling rapid AI development and experimentation.
- Identify threats unique to AI systems—model inversion, poisoning, evasion attacks, data leakage, prompt injection, etc.
- Evaluate emerging AI security threats, tools, and best practices.
- Lead AI-specific risk assessments and security design reviews.
- Work with red teams to validate model robustness against adversarial attacks.
- Establish security policies for ethical AI use. Ensure compliance with enterprise, industry, and regulatory frameworks (e.g., NIST AI RMF, GDPR, HIPAA, SOC2, ISO 42001).
- Partner with data science, platform engineering, cloud security, product, and compliance teams.
Requirements
- 10+ years in cybersecurity architecture or engineering roles
- Strong knowledge of modern AI/ML architectures, pipelines, and tooling
- Experience with LLM security, prompt safety testing, or generative AI governance
- Understanding of AI based attacks and threats
- Strong knowledge of data protection and controls required to protect data
- Knowledge of creating and communicating cybersecurity risks both in technical and non-technical manner
- Experience working in AI/ML or data engineering environments
- Proven track record designing enterprise security frameworks or architecture patterns
- Excellent communication with technical and non-technical stakeholders
- Strong analytical, problem-solving, and decision-making abilities
- Leadership skills to guide engineering teams and influence organizational policy
- Knowledge of regulatory frameworks specific to healthcare or finance (HIPAA, PCI, etc.)
Benefits
- 401k plan with employer match
- Flexible paid time off
- Holidays
- Parental leaves
- Life and disability insurance
- Health benefits including medical, dental, vision, and prescription drug coverage
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