Engineer, AI Security

LPL Financial•Charlotte, TX

2d•Hybrid

About The Position

The AI Security Engineer is responsible for securing enterprise AI platforms, AI-enabled applications, LLM technologies, and agentic workflows. This role ensures AI security technologies are operationally ready, integrated, and optimized to meet enterprise security and operational requirements. The position serves as a key intermediary between AI Engineering, Security Engineering, and Security Operations (SOC), translating AI security capabilities into engineering requirements, integration strategies, and operational enablement. Primary focus areas include platform readiness, telemetry integration, detection engineering, automation, and governance.

Requirements

5+ years of security engineering experience
3+ years supporting or partnering with Security Operations (SOC) functions
1+ year of experience with AI security technologies, LLM platforms, agentic systems, or AI-enabled workflows
Experience in cloud security monitoring, telemetry, and detection engineering
Experience building automation workflows and engineering solutions
Experience working within enterprise or regulated environments
Ability to communicate technical concepts and strategies to executive stakeholders
Experience integrating enterprise security platforms and operational tooling
Strong understanding of SIEM, SOAR, and security operations concepts

Nice To Haves

Experience with AI security monitoring platforms
Experience securing enterprise AI or GenAI deployments
Familiarity with AI-assisted engineering tools (e.g., Claude, Cursor)
Knowledge of prompt security, model governance, and agentic workflows
Experience in financial services or other regulated industries

Responsibilities

Establish and maintain AI security platform readiness across enterprise AI technologies, ensuring tools, sensors, and monitoring capabilities are fully operational and optimized
Validate functionality, configuration, and deployment readiness of AI security platforms and controls across cloud and endpoint environments
Drive continuous optimization of AI security tooling, integrations, and engineering practices aligned with enterprise standards
Define AI security engineering requirements to support SOC monitoring, detection, and response capabilities
Develop and operationalize AI-specific detection use cases, alerting logic, and prevention workflows
Enable integration of AI telemetry into SOC workflows and enterprise security operations
Build and mature AI incident response processes and escalation procedures
Partner with SOC teams to enhance detection engineering and overall operational effectiveness
Integrate AI security technologies with enterprise platforms including SIEM, SOAR, EDR, CSPM, CNAPP, and logging systems
Ensure interoperability between AI security controls and broader enterprise security tooling
Operationalize telemetry pipelines and observability standards for AI systems
Improve visibility into AI applications, model usage, prompt activity, and agent behavior
Partner with cloud and endpoint security teams to optimize cross-platform integrations
Establish governance frameworks and enforce security controls for AI systems operating in regulated environments
Ensure alignment with compliance, regulatory, and enterprise security requirements
Support audit readiness and validation of AI security controls
Define policies for AI usage, access, monitoring, and automation
Support risk assessments for AI platforms, integrations, and workflows
Identify opportunities to automate security engineering and SOC processes
Design and implement AI-assisted workflows using tools such as Claude, Cursor, and enterprise automation platforms
Develop scalable automation playbooks and orchestration processes to improve efficiency and consistency
Reduce manual effort through system integrations and workflow automation
Drive training and enablement across engineering teams for AI-assisted development and automation practices
Develop and promote best practices for secure AI engineering workflows
Create enablement materials, workshops, and repeatable standards for AI security adoption
Communicate AI security capabilities, risks, and priorities to technical and executive stakeholders
Support security leadership with AI security strategy and planning
Drive cross-functional alignment across Security, Engineering, Risk, and Architecture teams