Systems Engineer with years across IT, cybersecurity, SaaS operations, and emerging AI tooling. I've spent that time in the weeds — supporting real users, hardening real networks, and shipping automation that gave real hours back. What I do best is sit between teams, find the real problem, and build the solution — the systems integration, the automation, or the data dashboard that makes the whole team more productive.
In practice that means being the bridge between Customer Success, Engineering, and Product — working closely with teams and customers to capture the domain knowledge that turns a vague problem into a high-value solution.
Diagnose vague problems fast — logs, curl, DevTools, Wireshark, SQL debug. Reproduce, isolate, root-cause, then document — the underlying documentation that scales a team and saves the next engineer the same dig.
Builds data dashboards and refactored SQL queries so teams get real visibility and resolve issues faster. Data engineering and data enhancement that turn raw, messy sources into clean, decision-ready datasets.
Systems integrations and automation that replace manual work and reporting — REST APIs, webhooks, and SSO wiring services together, with Python, PowerShell, Bash, SQL, and Terraform behind them. Measurable hour-reductions on real workflows.
Windows (10/11/Server), Linux, Microsoft 365 (Graph API), Azure, AWS. I provision and automate Active Directory, manage identity in Auth0, codify infrastructure with Terraform, keep it observable with CloudWatch, and version everything in Git/GitHub.
TCP/IP, DNS, routers, firewalls — diagnose at the wire. Cybersecurity hardening with SIEM, EDR, MFA, IAM, and threat intelligence, plus virtualization and backups so issues don't become incidents.
Agentic AI applied to real engineering work — prompt engineering and LangGraph orchestration of LLMs behind production assistants, with RAG for grounded answers. Deployed where teams already work, including MS Teams, with guardrails like confirmation gates and audit logging.
Field logs from years building real IT, data, and AI systems — each linked out to the full write-up.