AI Security Engineer

SMBC Group is a top-tier global financial group. Headquartered in Tokyo and with a 400-year history, SMBC Group offers a diverse range of financial services, including banking, leasing, securities, credit cards, and consumer finance. The Group has more than 130 offices and 80,000 employees worldwide in nearly 40 countries. Sumitomo Mitsui Financial Group, Inc. (SMFG) is the holding company of SMBC Group, which is one of the three largest banking groups in Japan. SMFG’s shares trade on the Tokyo, Nagoya, and New York (NYSE: SMFG) stock exchanges. In the Americas, SMBC Group has a presence in the US, Canada, Mexico, Brazil, Chile, Colombia, and Peru. Backed by the capital strength of SMBC Group and the value of its relationships in Asia, the Group offers a range of commercial and investment banking services to its corporate, institutional, and municipal clients. It connects a diverse client base to local markets and the organization’s extensive global network. The Group’s operating companies in the Americas include Sumitomo Mitsui Banking Corp. (SMBC), SMBC Nikko Securities America, Inc., SMBC Capital Markets, Inc., SMBC MANUBANK, JRI America, Inc., SMBC Leasing and Finance, Inc., Banco Sumitomo Mitsui Brasileiro S.A., and Sumitomo Mitsui Finance and Leasing Co., Ltd. JOB SUMMARY As an AI Security Engineer, you will help secure the organization's AI, machine learning, generative AI, and agentic AI platforms. You will work with security, cloud, engineering, data, and risk teams to build security controls that protect AI systems throughout their lifecycle. This role focuses on identifying and reducing AI-specific risks while enabling the safe, compliant, and responsible adoption of AI technologies across the enterprise. PRINCIPAL DUTIES AND RESPONSIBILITIES Design, implement, and maintain security controls for generative AI, large language models (LLMs), AI agents, and machine learning platforms. Develop secure architecture patterns, standards, and guardrails for AI solutions across data ingestion, model development, deployment, and inference workflows. Integrate AI security requirements into software development, DevSecOps, and MLOps processes. Secure AI platforms and services, including Azure AI, Azure OpenAI, AWS Bedrock, Databricks AI, and related cloud-native technologies. Monitor AI environments by implementing logging, telemetry collection, threat detection, and security monitoring capabilities. Assess AI solutions for risks such as prompt injection, model poisoning, data leakage, adversarial attacks, unauthorized access, insecure agent behavior, retrieval-augmented generation (RAG) vulnerabilities, and third-party supply chain threats. Partner with architecture, engineering, data science, privacy, legal, compliance, and cloud teams to incorporate security requirements into solution design, deployment, and operations. Support AI security testing, red team exercises, incident response preparedness, control validation, and continuous improvement initiatives. POSITION SPECIFICATIONS Bachelor’s degree in Information Security, Computer Science, Engineering, or a related field, or an equivalent combination of education, certifications, and experience. 3 to 5 years of experience in cybersecurity, security engineering, cloud security, or security architecture. Experience designing and implementing security solutions in cloud environments such as Azure, AWS, or Google Cloud Platform (GCP). Knowledge of enterprise security concepts, including networking, operating systems, web applications, identity and access management, authentication, privileged access controls, and certificate management. Understanding of application security, API security, modern threat techniques, and cloud security risks. Familiarity with security and compliance frameworks such as NIST, OWASP, ISO, SOX, and SWIFT. Working knowledge of AI, machine learning, and generative AI technologies, including security considerations throughout the AI lifecycle. Strong written and verbal communication skills with the ability to explain technical concepts to both technical and non-technical audiences. Cloud Platforms Microsoft Azure Amazon Web Services (AWS) Google Cloud Platform (GCP) Identity & Access Management Active Directory Microsoft Entra ID (Azure Active Directory) Multi-factor authentication (MFA) Identity governance and privileged access management AI Security LLM and generative AI security AI governance and risk management Prompt injection and jailbreak protection Model security and data protection RAG and AI agent security NICE TO HAVE Hands-on experience with Azure OpenAI, AWS Bedrock, Databricks AI, or similar AI platforms. Experience implementing security controls within MLOps environments. Exposure to AI security testing, red teaming, or adversarial attack simulations. Security certifications such as CISSP, GSEC, GIAC, CEH, CSSLP, CCSP, or cloud security certifications. Advanced degree in Information Security, Cybersecurity, Computer Science, or a related discipline. SMBC’s employees participate in a Hybrid workforce model that provides employees with an opportunity to work from home, as well as, from an SMBC office. SMBC requires that employees live within a reasonable commuting distance of their office location. Prospective candidates will learn more about their specific hybrid work schedule during their interview process. Hybrid work may not be permitted for certain roles, including, for example, certain FINRA-registered roles for which in-office attendance for the entire workweek is required. SMBC provides reasonable accommodations during candidacy for applicants with disabilities consistent with applicable federal, state, and local law. If you need a reasonable accommodation during the application process, please let us know at .