Principal Cybersecurity Architect

CRC Group•Charlotte, NC

21h•Onsite

About The Position

The Principal Cybersecurity Architect will oversee the security architecture, design, and deployment of multiple information security technologies, including managed service security providers. This includes endpoint, application, cloud, network, AI/ML systems, and data protection design, documentation, and support of effective security engineering and security operations. The role is responsible for the implementation and management of cybersecurity in all public cloud environments, including security for generative AI services and LLM-based applications. The architect will interface with multiple Line of Business CIOs to develop and support innovative security solutions to minimize risk and streamline business processes. This position maintains responsible oversight of a dedicated team that will design security capabilities and operationally feasible solutions to enable the business and protect the enterprise. The role is responsible for delivering security architecture and engineering outcomes for the Cybersecurity organization and the Enterprise. The architect will work with stakeholders across the organization to securely meet the requirements of business initiatives and will serve as a technical authority on cloud, AI, and cybersecurity architecture for the Enterprise. The role will also oversee a managed security service provider supporting program efforts.

Requirements

Bachelor’s Degree
6+ years of cyber security architecture and engineering leadership experience
Previous leadership experience in medium sized to large teams
Knowledge of cybersecurity governance, design, and operations
Hands-on experience securing AI/ML systems, generative AI platforms, or LLM-based applications, with familiarity in AI security frameworks (e.g., NIST AI RMF, ISO/IEC 42001, OWASP Top 10 for LLMs, MITRE ATLAS).
Awareness of evolving AI regulation and guidance (e.g., EU AI Act, U.S. federal AI executive actions, state-level AI laws) and the ability to translate them into enterprise security requirements.
Strong ability to communicate via written and verbal communication in both formal and casual situations.
Ability to effectively communicate technical information and translate it between stakeholders.
Working knowledge of AI and machine learning concepts, with the ability to communicate AI risk, security trade-offs, and Responsible AI principles to both technical and business stakeholders.
Comfort using AI-assisted tools to accelerate architecture, engineering, and security operations work, with sound judgment for verifying outputs and managing model limitations.
Experience managing teams and vendors, driving SLAs; Experience with managing security with SaaS providers.
Self-starter who takes ownership and responsibility for prudent service delivery
Works independently with minimal guidance to drive projects to completion, while also working collaboratively with the team to achieve strategic goals.
Professional, clear, and concise verbal and written communication to internal customers, subject matter experts, upper management, and other audiences
A collaborative team player who will solicit and offer input and support decision-making.
Position requires access to sensitive confidential material; Integrity and discretion are mandatory.
Comfortable working in a continuously changing, fast-paced environment - balancing multiple priorities, special projects, and other activities.

Responsibilities

Manage vendor teams and drive discussions with various project teams, developers, and operations teams to ensure compliance with security guidelines and standards.
Experience with cyber security implementations within a major Cloud operating environment.
Experience developing and budgeting for cyber defense strategies that include dependencies on defense in depth principles.
Planning, studying and then designing a resistant security architecture for various IT initiatives.
Researching and implementing updated security standards, systems, and best practices.
Anticipating potential security threats by intaking strategic threat intelligence and acting upon it timely.
Managing technology road maps and security improvement/maturity projects.
Document and address organization's information security, cybersecurity architecture, and systems security engineering requirements throughout the acquisition life cycle.
Ensure that acquired or developed system(s) and architecture(s) are consistent with organization's cybersecurity architecture guidelines.
Identify and prioritize critical business functions in collaboration with organizational stakeholders.
Define and document how the implementation of a new system or new interfaces between systems impacts the security posture of the current environment.
Evaluate security architectures and designs to determine the adequacy of security design and architecture proposed or provided in response to requirements contained in acquisition documents.
Determine the protection needs (i.e., security controls) for the information system(s) and network(s) and document appropriately.
Experience in multi cloud security architecture. Primary focus in Azure.
Drive security controls with information security standards such as: NIST 800-53, NIST CSF, NIST AI Risk Management Framework (AI RMF), ISO/IEC 42001, OWASP Top 10 for LLMs, SOX, SOC2, and CIS Controls.
Understanding of Identity and Secrets Management, Logging and Monitoring, Application Security, Vulnerability Management, AI/ML Security (model risk, prompt injection defenses, training-data protection, and responsible AI controls) and Threat Detection and Response.
Lead the security architecture for AI and machine learning platforms, generative AI services, and large language model (LLM)–based applications, including controls for model integrity, prompt injection, training-data protection, model supply chain risk, and unauthorized model or API access.
Establish and govern enterprise standards for the secure adoption of AI, including third-party AI services, copilots, and embedded AI capabilities within SaaS platforms; partner with Legal, Privacy, and Compliance to operationalize Responsible AI and acceptable-use policies.
Partner with Data, Analytics, and AI Engineering teams to embed security-by-design and privacy-by-design into AI/ML pipelines, training datasets, model development, deployment, and ongoing monitoring for drift, abuse, and emerging threats.
Evaluate and integrate AI-augmented security tooling (e.g., AI-driven detection and response, vulnerability management, identity analytics, and SOC automation) into the enterprise security architecture, while managing risks such as model bias, hallucination, and explainability.
Anticipate AI-specific threats (e.g., adversarial machine learning, model theft, data poisoning, prompt injection, deepfakes) and translate emerging AI regulations and standards into actionable security architecture and engineering requirements.