Senior AI Security Architect

Sumitomo Mitsui Banking Corporation•Charlotte, NC

2d•Hybrid

About The Position

As the Senior AI Security Architect, you will lead the design, governance, and advancement of the enterprise AI security architecture program. You will define security strategy, architecture standards, governance models, and technical controls that enable the organization to adopt Artificial Intelligence (AI), Generative AI, Machine Learning, and Agentic AI securely and responsibly. This role combines strategic leadership with deep technical architecture expertise and serves as the senior security authority for AI-related initiatives across the enterprise. You will partner closely with engineering, cloud, data, model risk, privacy, legal, compliance, cyber defense, and business teams to ensure security is embedded throughout the AI lifecycle while supporting innovation, regulatory compliance, and business objectives.

Requirements

Bachelor’s degree in Information Security, Cybersecurity, Computer Science, Engineering, Artificial Intelligence, or a related field, or equivalent combination of education, certifications, and experience.
12+ years of experience in cybersecurity, security architecture, secure engineering, technology risk management, or related disciplines.
7+ years of experience leading enterprise security architecture initiatives, architecture teams, or strategic cybersecurity programs.
Strong knowledge of enterprise security architecture, networking, operating systems, web applications, APIs, software development, automation, cloud security, and modern cybersecurity practices.
Experience performing architecture reviews, threat modeling, risk analysis, security assessments, and control design across complex enterprise environments.
Deep understanding of cyber threats, attack techniques, security monitoring, incident response, penetration testing, red teaming, and security control validation.
Experience designing and securing cloud environments, including AWS, Microsoft Azure, and Google Cloud Platform.
Strong knowledge of identity and access management, including Active Directory, Azure Active Directory, identity governance, multi-factor authentication, certificate management, machine identities, and privileged access controls.
Deep understanding of AI, Machine Learning, Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), model operations, and Agentic AI architectures.
Experience securing AI-enabled applications, APIs, model integrations, cloud-native services, AI platforms, and third-party AI capabilities.
Knowledge of AI-specific security risks and controls, including prompt security, model integrity, adversarial machine learning, AI governance, model monitoring, and runtime security controls.
Experience supporting audits, regulatory assessments, governance reviews, and risk management activities within highly regulated industries.
Experience aligning AI and cybersecurity controls with frameworks such as NIST, ISO, OWASP, SOX, SWIFT, AI risk management frameworks, model risk management standards, and applicable regulatory requirements.
Strong executive communication and stakeholder management skills with the ability to explain complex technical concepts and risks to senior management and business leaders.
Understanding of third-party AI risk, model provenance, responsible AI principles, data governance, privacy obligations, and enterprise governance processes.
Experience developing security standards, architecture principles, reference architectures, and governance frameworks for enterprise technology initiatives.

Nice To Haves

Professional certifications such as CISSP, CISM, CCSP, GIAC, GSEC, CSSLP, SABSA, cloud security certifications, or AI governance certifications a plus.

Responsibilities

Define and maintain the enterprise AI security architecture strategy, standards, reference architectures, and guardrails for AI, Generative AI, Machine Learning, and Agentic AI solutions.
Lead the design of secure-by-design architecture patterns across data ingestion, model development, model training, deployment, inference, Retrieval-Augmented Generation (RAG), agent orchestration, and ongoing operations.
Conduct and oversee AI security architecture reviews, threat models, and risk assessments for enterprise AI platforms, business applications, cloud AI services, third-party AI providers, and open-source AI technologies.
Identify and mitigate AI-specific threats, including prompt injection, jailbreaking, model poisoning, adversarial attacks, model inversion, unauthorized model access, excessive agent autonomy, sensitive data exposure, and AI supply chain risks.
Establish and strengthen security controls for AI platforms, cloud environments, identity and access management, privileged access management, secrets management, data protection, monitoring, logging, model lifecycle security, and runtime enforcement capabilities.
Develop enterprise reference architectures and governance requirements for foundation models, third-party AI services, AI-enabled business solutions, autonomous agents, and emerging AI technologies.
Partner with architecture, engineering, cloud, data, privacy, legal, compliance, model risk, and cyber defense teams to integrate AI security requirements into solution design, development, testing, deployment, monitoring, and operational processes.
Serve as the senior AI security architect and trusted advisor to executive leadership, governance committees, and technology stakeholders on AI security risks, control requirements, regulatory expectations, and architectural decisions.
Define architecture requirements for Agentic AI solutions, including authorization boundaries, tool access controls, human oversight requirements, audit logging, runtime monitoring, and containment mechanisms.
Lead AI threat modeling, security assessments, red teaming activities, control validation exercises, and security reviews for high-risk AI implementations.
Evaluate emerging AI technologies and security capabilities and provide strategic recommendations regarding enterprise adoption, risk management, and security architecture direction.
Support regulatory examinations, audits, risk assessments, and governance reviews by defining security controls, architecture standards, and evidence requirements for AI-enabled solutions.