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Role-Specific Resume

Nicholas Francis O'Brien | AI / Process Improvement

AI-assisted operations and process improvement | IT Service Desk Analyst | Wellington, New Zealand

AI-assisted operations and process improvement

Professional Summary

Enterprise IT support professional applying AI-assisted research, scripting, documentation, and structured troubleshooting to operational support problems.

Uses AI as a practical delivery aid for fault analysis, remediation design, workflow mapping, documentation, automation enablement, and escalation quality.

Well suited to evolving operational environments where loose problems need to become documented workflows, scripts, decisions, or repeatable outputs.

Key Terms and Skills

  • AI-assisted operations: research, troubleshooting, scripting, documentation, remediation logic, playbooks, automation-ready handoff
  • Process improvement: workflow traceability, process mapping, ticket linkage, repeatable guidance, documentation quality, handoff clarity
  • Enterprise investigation: vendor applications, packaged installs, application faults, deployment symptoms, endpoint-state evidence
  • Operational delivery: ServiceNow, Jira Service Management, incident/request handling, remote/admin tools, PowerShell tooling

Selected Experience

  • Improved operational traceability through bulk updates, filtering, and cross-ticket linkage.
  • Used AI-assisted drafting and analysis to turn troubleshooting results into clearer documentation and repeatable guidance.
  • Converted recurring support failures into remediation logic, documentation, and deployment evidence for automation-ready handoff.
  • Supported printer vendor transition work and resolved configuration issues beyond normal front-line scope.
  • Applied remediation evidence to improve handoff quality where access, ownership, or packaging boundaries required escalation.
  • Supported users in a 5,000+ user enterprise environment across shared-service support operations.
  • Owned incidents and service requests from diagnosis through resolution, documentation, or evidence-based escalation.

Selected Evidence

  • Investigated a recurring vendor application endpoint failure through controlled manual testing. Used AI-assisted research and scripting to convert findings into a PowerShell remediation path.
  • Mapped safe remediation handling for application folders, cache contents, and local state files. Validated what could be cleared, regenerated, or preserved before production use.
  • Documented the remediation process and circulated guidance to relevant teams. Recognised internally for initiative, clarity, and manager endorsement.
  • Used AI-assisted investigation to convert a recurring support failure into an internal remediation path, reducing dependency on higher-tier or external-vendor investigation.
  • Built the remediation logic and evidence base needed to make package-level deployment automation actionable.
  • Building AI-forward portfolio, resume projection, and canonical profile workflows with deterministic PDF and machine-readable profile outputs.
  • Developing data visualization, assistant-design, Linux support, and AI governance projects as applied AI systems practice.
  • Uses self-directed AI systems projects to strengthen prompting, workflow design, documentation, deterministic outputs, technical communication, and operational analysis.

Qualifications

  • NTT internal training via Skillsoft Percipio, including Azure AI, AI development, Microsoft Azure Fundamentals preparation, implementation strategy, service management, security awareness, and enterprise IT support coursework.
  • AWS Certified Cloud Practitioner | AWS Foundations of Cloud Computing — Unitec / Te Pūkenga
  • BA History and Political Science — Griffith University

Contact and Public Profile