I build systems that hold up under real traffic.
[SYSTEM BRIEF] Software Systems & DevSecOps Engineer.
[ENV] Linux / React Native / Node.js / Python / Laravel.
[INFRA] Cloud automation engineered via AWS, GCP, Terraform, and Docker.
[STATUS] Human intervention deprecated. Continuous deployment active.
• Built a fully automated CI/CD pipeline that runs static analysis with Semgrep and secret scanning with
TruffleHog on every push, blocking deployments on critical findings.
• Piped scan results to an LLM via API to analyze vulnerabilities in context and auto-generate pull
requests with remediation code, cutting manual triage time to zero.
• Provisioned AWS infrastructure as code with Terraform and implemented a scheduled GitHub Actions
workflow to detect configuration drift, sending Slack alerts when live state diverges from declared
config.
• Enforced infrastructure immutability by automating terraform plan checks on every commit, preventing
unreviewed manual changes from reaching production.
| Period | Degree / Specialization | Institution |
|---|---|---|
| Present | M.Sc. Cyber Security with AI | University of Lancashire (UK, Remote) |
| Completed | B.Sc. Computer Science | Memorial University of Newfoundland (Canada) |
• 8-Week course covering LLM threat modeling, prompt injection defense, AI agent hardening, CI/CD-based
vulnerability remediation, and using LLMs for log analysis.
• Capstone: Secured a Django application with LLM integration by identifying and fixing AI-specific risks
and traditional vulnerabilities improving overall system reliability and protecting sensitive data.
• 2-Months comprehensive training in Python, Probability & Statistics, Deep Learning, and NLP.
• Capstone: Developed a telecom churn prediction system to analyze customer retention, deploying the
solution via Streamlit.