Resume

University of Saint Mary

• Four-year cybersecurity program covering network security, operating systems, cryptography, digital forensics, and security operations
• Coursework in risk management, incident response, and legal/ethical frameworks
• Collegiate Esports Team - named 2025 Player of the Year
• Collegiate Football Team
• Leadership Club

CompTIA

Google / Coursera

CompTIA

Microsoft

TryHackMe

Microsoft

CompTIA

• Built a Python-based AI SOC analyst tool using SIEM indexer API, OpenAI, and structured JSON parsing to automate alert triage
• Resolved infrastructure issues including VM network configuration, NetworkManager troubleshooting, and SIEM indexer bind-address changes
• Tools: Python, OpenAI API, Wazuh Indexer, Rocky Linux, REST APIs

• Deployed a Windows 11 Pro VM in Azure and conducted credentialed vs. unauthenticated Tenable scans
• Credentialed scan revealed 147 vulnerabilities vs. 36 unauthenticated, demonstrating the value of authenticated scanning
• Tools: Tenable, Microsoft Azure, Windows 11, Network Security Groups, CVSS

• Diagnosed and resolved unreachable server VM through layer-by-layer investigation of VM power state, console access, interface configuration, routing, and NetworkManager profile activation
• Tools: Rocky Linux, nmcli, ip addr/route, Xen Orchestra, SSH

• Designed and operated a multi-server environment using XenServer virtualization, CentOS Linux, BungeeCord proxy, port forwarding, and DMZ configuration
• Wrote custom Java plugins with SQL-backed data persistence; managed team of 8-10 people
• Tools: CentOS, XenServer, SSH, Java, SQL, Port Forwarding, DMZ

• Built and iteratively refined a structured AI-assisted analysis workflow starting in 2023, developing prompt engineering techniques to reduce hallucinations and control model behavior
• Identified and resolved AI reliability failures by controlling information sourcing - providing verified data directly rather than allowing the model to retrieve from potentially outdated external sources
• Applied constraint engineering, step-by-step reasoning gates, and verified-vs-assumed output separation to improve analytical accuracy over multiple years of iteration
• Core insight: AI output quality is a direct function of input data quality and information access control - a principle that applies directly to AI-assisted security tooling
• Tools: ChatGPT / GPT-4, Structured Prompting, Manual Data Sourcing, Iterative Testing