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{{% resume/section "Summary" %}}
**Customer-focused call centre** professional with **Tier 1/2 support**
experience, **de-escalation**, and **clear communication**. Improves
**first-response**, reduces **escalations**, and shortens **resolution times**
across **high-volume phone/chat/email** queues. Strong **documentation habits**
and **plain-language** explanations for non-technical users.
{{% /resume/section %}}
{{% resume/section "Work Experience" %}}
{{% resume/work-experience
name="Red Hat"
title="Technical Support Engineer Intern (Tier 1/2)"
languages="Ticketing/Triage, De-escalation, Knowledge Base Writing"
date="Aug 2022 — Aug 2024"
%}}
- Delivered **Tier 1/2 frontline support** for CI/CD and Kubernetes issues via a ticket queue, improving **first-response time by 40%** through better triage and routing.
- Performed **incident troubleshooting and root-cause analysis**; automated data capture/validation that resolved **80% of config errors** and **reduced downtime by 40%**.
- Wrote **clear, step-by-step knowledge-base articles** and troubleshooting flows that enabled Tier 1 to solve common probe issues, **cutting escalations by 30%**.
- Built a deployment **runbook** that standardized fixes and **reduced repeat contacts/tickets by 66%**; **shortened resolution time from 45 → 15 minutes**.
- Kept users informed with **concise status updates**, set expectations, and **de-escalated frustrated stakeholders** by focusing on next steps and time to resolution.
- Partnered with QA/DevOps to capture **root causes** of startup failures; implemented dynamic probes that **cut production launch issues by 50%**.
- **Reduced deployment time by 66%** by implementing a
[solution](https://github.com/apache/incubator-kie-kogito-operator/commit/175a6356c5474f2360ccb8ae835e0b9b2d653cf1) for deploying locally-compiled binaries onto
Kubernetes/OpenShift via command-line, **cutting average
deployment times from 45 minutes to 15 minutes**.
(**Kubernetes/GoLang** used for this and three below).
- **Eliminated 80% of manual configuration errors** by enabling
the Kubernetes operator to automatically fetch data from
deployed services and update configurations, **deprecating
legacy startup scripts and reducing overall startup time
by 40%**.
- **Improved application stability** by introducing startup
probes for legacy applications with longer boot times,
**resulting in a 50% reduction in startup-related failures
and downtime during production launches**.
- **Enhanced system reliability** by refactoring probes to
[assign default values](https://github.com/apache/incubator-kie-kogito-operator/commit/af4977af228ec8648be28779259d4552246b656f) dynamically based on deployed YAML
files and fixing reconciliation issues, **increasing probe accuracy by 30%** and preventing misconfigurations.
- **Increased CI pipeline efficiency** by rewriting the
**Jenkins (Groovy)** [nightly pipeline](https://github.com/apache/incubator-kie-kogito-pipelines/commit/4c83f1aecdea2c1ba2796b79839a90d4083dce88) to run in a GitHub PR
environment, allowing for automated testing of all
team-submitted PRs prior to merging, **reducing manual
intervention by 60%**.
- **Increased project reproducibility** by taking initiative to
write a [reusable GitHub parameters file](https://github.com/apache/incubator-kie-kogito-pipelines/commit/4c83f1aecdea2c1ba2796b79839a90d4083dce88#diff-7d2c018dafbccec859077d19bf1ade53ec9c7649f235528ce89f5632b109f7e6) for the pipeline,
**enabling 100% reusability** and ensuring consistent pipeline
setups across different environments.
- **Streamlined developer onboarding** by authoring
comprehensive [project documentation](https://github.com/apache/incubator-kie-kogito-operator/blob/1534c03d1d26bec08a16608a775782bf8b305de9/docs/GUIDE_FOR_KOGITO_DEVS.md) and mentoring an
incoming intern, **reducing onboarding time by 50%** and
enhancing new team members' productivity within their
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