AI Security Technical Architect
Role details
Job location
Tech stack
Job description
We are seeking a Sr. AI Security Technical Architect to own and evolve the enterprise AI security architecture and strategy. This role involves aligning business goals with technology platforms and risk management practices. The ideal candidate will translate business requirements into security requirements, define security controls for AI, and develop standards, policies, and high-level approaches for engineering teams., * Own and evolve the enterprise AI security architecture and strategy, aligning business goals, technology platforms, and risk management practices.
- Assist in defining secure-by-design patterns and standards for AI/ML systems.
- Establish and maintain AI-specific security artifacts.
- Ensure consistent adoption of NIST AI RMF, MITRE ATLAS, CIS, and ISO 27001 across AI initiatives.
- Establish architectural governance and enforce adherence to AI security standards.
- Influence AI design decisions early in the lifecycle to reduce risk.
- Partner with enterprise stakeholders to balance innovation with risk tolerance.
- Evaluate AI frameworks, agents, vector databases, and third-party AI platforms for security posture.
- Recommend and rationalize AI security tooling as part of the enterprise security strategy.
- Monitor emerging AI threats, regulatory guidance, and industry best practices to inform security strategy.
Requirements
Education: A Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience is required.
Experience: This position requires 8-12+ years of experience in cybersecurity engineering or architecture within a complex enterprise environment, including 2-4+ years of hands-on experience securing or reviewing AI/ML systems and platforms.
Technical Skills: A strong understanding is needed of LLM architectures, embeddings, Retrieval-Augmented Generation (RAG) patterns, end-to-end ML pipelines, AI model supply chain risks, Zero Trust and identity-centric security models, and cloud security across Azure, AWS, and Google Cloud Platform. Proven ability to influence architecture decisions and lead cross-functional initiatives is necessary.
Preferred Qualifications
- Security certifications such as CISSP, CISM, CCSP, or SANS certifications.
- Experience contributing to responsible AI practices, explainability, or bias mitigation initiatives.
- Experience securing AI platforms in regulated industries, particularly financial services.
- Background supporting advanced encryption, cryptographic agility, or post-quantum readiness.
- Demonstrated experience in incident response and enterprise risk management.
- Understanding of various regulatory requirements and laws, including but not limited to NYDFS Cybersecurity Regulations and FINRA Regulations