{{% resume/section "Web Dev Projects" %}}<!--- {{{ -->
{{% 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.
rarity rankings for NFT's, integrating with **leading
marketplace's API** to enable users to quickly identify
rare NFT's and check their listing status, **improving
market research efficiency by 80%**.
- **Built a scalable [Node.js backend](https://github.com/Rarity-Surf/ME-sniper-backend)** with REST API
endpoints to return NFTs based on customizable filters
such as max rank, price, and rarest traits. **Optimized
performance** to handle **3,000+ concurrent requests** by
implementing efficient data fetching and caching
mechanisms using **PostgreSQL** , ensuring low-latency
access to NFT data.
- **Built a dynamic [React frontend](https://github.com/Rarity-Surf/ME-sniper-frontend) (TypeScript/JavaScript)** to load and display NFTs in real-time with user-defined filters. Styled
using a mobile-responsive library, **reducing load times by 50%**.
- **Developed a [Discord bot](https://github.com/Rarity-Surf/ME-sniper-discord-bot) (TypeScript/JavaScript/Node.js)** to notify users of profitable
resale opportunities by leveraging historical sales data
to assess deal quality. This feature **increased user
engagement by 80%** and provided a seamless way for users
to stay updated on market opportunities.
- Built and managed a **peer-to-peer e-commerce operation** reselling digital items; exceeded **$50,000+ gross merchandise
value**.
- Closed transactions and **middlemanned for high-value trades exceeding $5,000+ deals)** with **250+ verified vouches**, maintaining **5-star satisfaction** and **zero unresolved disputes**.
- Handled **end-to-end operations and escrow**: sourcing, pricing, inventory, listings, secure payments and fulfillment.
- Implemented **fair-value pricing** and **bundle offers** to accelerate turnover and improve margins while reducing low-value inquiries.
- Standardized **ownership verification and middleman workflows** to mitigate **fraud/chargeback** risk on large trades.
- Tracked **P&L and cash flow**; reconciled payments and maintained records for auditability.
{{% 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%**.
- Reproduced user-reported issues; wrote **concise repro steps** and a **known-issues + workarounds** note to reduce repeat questions.
- Partnered with devs to **prioritize fixes** from impact-driven triage and shipped **onboarding/troubleshooting snippets** that cut new-user setup pings, improved first-contact resolution, and kept user-facing notes up to date.
- **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%** (**Kubernetes/GoLang** used for this and three below).
- **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**.
- **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**.
- **Improved system reliability** by refactoring probes to dynamically assign default values based on YAML files, **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
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