Ahmed AlOtaibi

QA Engineer | iOS Developer

At Apple, I turned recurring customer-reported problems into documented bug reports—and reproduced software issues and verified fixes in QA.

≈1,200
customers supported in one quarter
98/100
NPS score
150+
employees supported through training
Portrait of Ahmed AlOtaibi

More at Apple

Technical support, training, and sales experience alongside hands-on QA work.

Nov 2021 — Jul 2026
San Francisco, CA

Technical Specialist | Genius Bar

At a high-volume Genius Bar, I typically handled 35–40 appointments a day, while many teammates handled about 15–20. In my final quarter, I supported approximately 1,200 customers, ranked #1 in appointments handled, and earned a 98/100 NPS. Alongside my own workload, I watched for stalled visits and stepped in to help teammates move appointments forward. I also documented recurring device issues with reproduction details and escalated patterns through Apple’s internal channels.

Technical supportmacOS / iOSTroubleshootingEscalation
Feb 2023 — Aug 2023
San Francisco, CA

Training In-Store Experience

I led store learning sessions on Apple updates, products, and features, including morning meetings and small-group workshops. I explained technical concepts such as the Neural Engine and discussed the growing use of AI in everyday tools, helping teammates present features clearly and tailor recommendations to customers’ needs.

I supported more than 150 employees through required and assigned training. I built an Excel tracker, checked completion with employees, followed up during the week, and arranged time off the floor or one-on-one coaching when needed. Completion typically reached 95–98%. After the store leader’s reports matched my tracker for a week or two, the leader came to rely on it for progress updates; a market leader later refined the tracker and shared it with other stores.

TrainingEnablementDocumentation
Jul 2021 — Nov 2021
San Francisco, CA

Seasonal Sales Specialist

I asked customers how they used their current device and what they needed from an upgrade, then recommended a product that fit. For example, I recommended a standard MacBook Air to college students who mainly needed a computer for coursework, explaining why they did not need to pay for higher-end specifications they were unlikely to use. I translated technical concepts such as unified memory into clear language and focused on value and fit rather than upselling. My product knowledge and customer communication helped me earn the opportunity to move to the Genius Bar.

Customer discoveryProduct knowledgeClear communication

Projects

A selection of iOS, QA, and AI-workflow projects. Where AI-assisted implementation was used, my role focused on requirements, acceptance criteria, validation, and release decisions.

Native iOS · Live on the App Store

KXSF.FM (San Francisco Community Radio iOS app)

KXSF.FM is the iOS app for San Francisco Community Radio. I built and released V1 so listeners could stream KXSF live. For V2, I used station feedback to define show information, a weekly schedule, YouTube livestream access, and station details, then tested the completed experience on a real iPhone.

SwiftAVFoundationiOSApp Store release
Local-first
AI evaluation

AI Output Review Tool

Defined the product scope, evaluation criteria, local-first requirements, and acceptance tests for an AI-agent-assisted QA workspace for scoring AI responses and classifying failure patterns. The browser-based tool stores searchable review history locally and does not call an external AI provider.

AI evaluationJavaScriptTest-driven QA
Technical operations
Human-approved

Multi-Agent AI Operations & Knowledge Systems

Designed specialist AI workflows with a shared knowledge base, role-specific write boundaries, operator review, and human approval for conflicting facts. Defined the system’s responsibilities and checked its behavior; AI assistants substantially helped implement it.

Agent operationsEvidence reviewAPI troubleshooting

Best fit

QA Analyst / QA EngineeriOS Developer / Software Engineering

Looking for an evidence-led technical problem solver?

At the Genius Bar, I diagnosed customer problems, documented recurring device issues, and helped teammates keep appointments moving. In Apple QA, I reproduced software failures and verified fixes. I’m looking for QA or iOS work where customer experience and product quality meet. If that’s what your team needs, let’s talk.