Cyber Security Architect - Generative AI Specialist
At Regions, the Cyber Security Architect contributes to the advancement of Regions' cyber security program and its capabilities through developing, communicating, and implementing a security architecture. This position establishes secure development practices which increases the security of internal systems. Additionally, this position collaborates closely with key stakeholders and teams as part of business projects and / or initiatives.
The Cyber Security Architect will be a subject-matter expert for securing GenAI capabilities (LLM APIs, agent frameworks, RAG pipelines, MCP-based tools, and Agentic AI). The architect will design controls that protect data, ensure safe tool use, and meet emerging AI-specific regulations and standards.
Primary Responsibilities
- Develops and establishes a strategic cyber security architecture and strategic vision, including standards and frameworks that are aligned with the overall business and Regions' information technology strategy
- Provides advisory and consultative services to businesses, information technology groups, and cyber security senior leadership
- Works closely with Enterprise Architecture and Application Development groups to enhance the security posture of new and existing systems
- Designs cyber security architecture, evaluates and mitigates potential risk, and approves implementation of systems and applications into production
- Performs assessments using the National Institute of Standards and Technology (NIST) Cyber Security Framework and the Federal Financial Institutions Examination Council (FFIEC) Cyber Assessment Tool to identify gaps and remediate deficiencies
- Ensures systems and applications are implemented with compensating controls to meet regulatory requirements (e.g. GLBA, SOX, HIPPA, FFIEC, etc.) as well as other organizational compliance (PCI) requirements
- Tracks metrics for compliance to internal cyber security standards set by application and system owners
- Provides consultative services related to large business projects
- May lead the work of junior architects and evaluate needs, assisting in the development of necessary skills and technical knowledge
Requirements
Bachelor's degree in Computer Science, or related fieldSeven (7) years of experience in cyber security, with a focus on software development, secure software development lifecycle (SDLC), or security architecturePreferences
Experience in the design and implementation of cyber security solutionsSkills And Competencies
Ability to effectively evaluate risk vs. rewardAbility to independently problem solve with sound judgementAbility to translate complex technical information across all levels of the organization through communications and / or presentationsAbility to work in a team environment when applicableAdvanced knowledge of risks associated with virtualization and cloud-based computing and the impact of those technologies on an organizations security postureAdvanced knowledge of security principles, solutions, tools, methodologies, and techniquesProficiency in Microsoft Office (Excel, Word, PowerPoint, Outlook, etc.)Strong project management skillsStrong verbal, written communication, and organizational skillsStrong work ethic and self-motivationAdditional Job Description
Architecting secure cloud workloads in AWS and / or Azure : prior demonstrable work designing and securing production systems.Architecting secure LLM integrations across clouds and model providers — e.g., using AWS Bedrock (e.g., Anthropic Claude, Meta Llama, Cohere, Titan), Azure OpenAI Service (OpenAI GPT), etc.Securing Agentic AI workflows : understanding how autonomous / semi-autonomous agents interact with tools, APIs, and enterprise data; mitigating risks like over-permissioning, SSRF, and data exfiltration through sandboxing, scoped tokens, allowlists, and execution monitoring.Designing and governing RAG pipelines : applying data classification, PII scrubbing, retrieval allow / deny rules, prompt templating, grounding policies, vector DB access control / rotation, query-time guardrails, and ensuring retention, lineage, consent, copyright compliance, secrets handling in prompts, and tenant isolation for embeddings / vector stores.Threat-modeling GenAI systems using OWASP Top 10 for LLMs / GenAI and MITRE ATLAS; addressing risks such as prompt injection, insecure output handling, data poisoning, model / data exfiltration, model DoS / cost abuse, supply-chain risks, and model extraction.Monitoring model quality and responses : designing automated evaluation pipelines (e.g., LLM-as-a-judge, bias / toxicity / factual accuracy checks), establishing continuous monitoring in production, and integrating human-in-the-loop escalation for sensitive outputs.Securing Model Context Protocol (MCP) implementations : applying authentication / authorization, scoping, sandboxing, and auditing for tool / data access.Applying security frameworks and guidance such as NIST AI RMF & Generative AI Profile, OWASP Top 10 for LLMs, MITRE ATLAS, Google SAIF, and UK NCSC AI security guidance.Applying governance and regulatory frameworks such as ISO / IEC 42001 AI Management SystemEqual Opportunity Employer / including Disabled / Veterans
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