Virginia Beach, Virginia, United States
Senior Security Engineer | AI & Cloud Security Specialist I help organizations reduce risk and stay audit-ready by building proactive, real-time defenses across physical, network, cloud, and AI/LLM environments. Over the past 5+ years I've worked across finance, healthcare, tech, and consulting — currently securing a regulated financial institution's network as a Network Security Engineer at TowneBank. A few things I focus on: Security Architecture & Engineering — I design and deploy firewall, SIEM, EDR/NDR/XDR, and SASE solutions (Palo Alto, Cisco Secure Firewall, Splunk, Microsoft Sentinel, CrowdStrike, SentinelOne, Zscaler) that shrink response time and harden enterprise defenses. Cloud Security — Hands-on experience securing AWS, Azure, and Microsoft 365 environments, including identity/access controls and cloud-native threat detection. AI/LLM Security — A less common specialty I've built real experience in: I served as Security SME for a major AI lab, reviewing model outputs for PII leakage and helping build guardrails that reduced error rates in production LLM/agentic systems. Compliance & Risk — Comfortable working within HIPAA, GLBA, SOX, GDPR, PCI DSS, CMMC, NIST and ISO security and regulatory frameworks. I'm currently exploring senior security engineering, architecture, and leadership roles where I can take ownership or support enterprise-wide security strategy. Always happy to connect with fellow security professionals, hiring managers, or recruiters — feel free to reach out.
- Architect, deploy, and manage enterprise Firewalls, NDR, and SASE security infrastructure across a 1,500–5,000 endpoint regulated financial institution, ensuring continuous alignment with GLBA, SOX, PCI DSS, and FFIEC requirements. - Lead and independently drive security initiatives including platform optimizations, security standards development, and control documentation. Coordinating cross-functional resources and aligning Engineering and InfoSec teams on execution. - Support enterprise security architecture and design across network, systems, and cloud security domains. Contributing to product evaluations, standards documentation, security design decisions, and control implementation. - Provide high level strategy and direction to TowneBank's AI security initiative, authoring AI security documentation, security testing frameworks, and product evaluation criteria for emerging AI and ML-integrated technologies. - Monitor and analyze network traffic across multi-segment enterprise environments to detect configuration conflicts, anomalous behavior, and malicious activity — driving rapid threat identification and remediation. - Serve as primary liaison between the engineering team and the broader InfoSec department, bridging technical implementation with security governance and policies to ensure cohesive enterprise-wide security outcomes.
- Served as Security SME and prompt optimization specialist for a major AI lab, evaluating LLM outputs across text, image, and document modalities to ensure responses were accurate, optimal, and aligned to prompt intent across a broad range of use cases. - Performed prompt rating, prompt analysis, and prompt optimization to improve model response quality, assessing output accuracy, relevance, and instruction following across diverse prompt types and use cases at scale. - Led security-focused model testing to prevent unauthorized disclosure of PII, financial data, and sensitive information from model-connected databases, designing and executing test cases that identified and closed critical data leakage vectors. - Enforced data boundary controls by testing and validating that LLM systems were not retrieving from unauthorized or unrestricted data sources, ensuring model behavior remained within defined security and compliance guardrails. - Injected structured security domain knowledge into model training pipelines as subject matter expert, improving LLM accuracy and response quality on cybersecurity topics including threat detection, incident response, and security best practices. - Collaborated cross-functionally with AI engineering and product teams to identify model performance bottlenecks, reduce error rates, and optimize agentic system outputs, directly improving response reliability and user trust at scale.
- Responded promptly to 911 calls, ensuring rapid on-site arrival. - Expertly drove ambulances, maintaining safety and efficiency. - Provided immediate emergency care, effectively containing injuries Documented incidents, ensuring accurate record-keeping. - Communicated patient information, enabling seamless handovers to medical staff.