Description
A student opens the app to begin their lesson, but the screen stays blank. A guide's mastery dashboard displays incorrect scores. L1 support and the AI have both attempted a resolution without success. The case now belongs to you — and a child's learning session depends on your ability to identify the actual issue.
The majority of your working time is spent on tickets that no one else managed to resolve, spanning the multiple applications that comprise Alpha's learning platform. Your process: recreate the failure in an environment matching the student's or guide's configuration, examine logs and documentation, deploy AI to accelerate diagnosis, then validate every output it provides — because an incorrect response delivered to a classroom scales its impact rapidly. Expect to onboard to a different product nearly every week. That cadence defines the role, not an obstacle to avoid.
Each issue is yours from start to finish: replicate it, determine root cause, and close it in the minimum number of interactions required to restore functionality for the student or guide. The diagnostic logic you document improves both the next agent's efficiency and the next AI automation, meaning your solution continues to deliver value well beyond the current ticket. With experience, you will become the escalation point for the team's most challenging education-product cases.
If you are drawn to difficult, open-ended problems, and you genuinely care that the product ultimately serves a child's education, submit your application.
What you will be doing
- Close complex, escalated cases from students, parents, and guides that neither AI nor L1 support were able to resolve.
- Replicate user-reported failures in an environment that matches the device, app version, and settings, using logs and actual user artifacts.
- Investigate across Alpha's suite of learning applications (ticketing systems, Slack channels, knowledge repositories, logs) before routing to engineering.
- Guide AI assistants (for example, ChatGPT or Claude) to accelerate root-cause analysis, anchor them in verified documentation, and confirm every recommendation.
- Engage with non-technical users in clear, patient language, collecting sufficient detail upfront to achieve single-touch resolution.
- Escalate to engineering with complete diagnostic context only when a defect in the product is confirmed.
- Record your diagnostic reasoning so future team members and AI workflows can leverage it.
What you will NOT be doing
- Working from scripts or rigid decision flowcharts for a single application.
- Processing the simple ticket queue. AI already handles cases solvable by knowledge-base lookup.
- Passing difficult issues to engineering without first replicating and isolating them yourself.
- Relying on AI to reason for you, or forwarding its suggestions without verification.
- Waiting for instruction or external intervention to move forward.
Key responsibilities
Own and resolve ambiguous, technically complex customer issues to root cause across Alpha's portfolio of education products.
Candidate requirements
- 2+ years of hands-on experience in a technical capacity such as technical support, software engineering, QA, sysadmin, or DevOps. Your exact job title need not have been "support."
- Proficiency constructing and interpreting REST API calls and JSON payloads, understanding HTTP status codes (for example, 401 vs 404 and 429 vs 403), and operating within command-line interfaces and log files.
- Demonstrated use of AI tools (for example, ChatGPT or Claude) as part of your regular technical workflow.
- Professional-level fluency in written and spoken English.
- Availability to work full-time (40 hours per week), with all hours scheduled between 1:00 PM – 10:00 PM UTC (8:00 AM – 5:00 PM US Eastern).
Nice to have
- Background supporting non-technical end users (in education, edtech, or consumer applications), rather than solely IT practitioners.
- Practical experience steering AI tools and identifying their errors.
- History of troubleshooting across multiple unrelated products, not confined to a single platform.
- Developer-level technical depth: ability to read source code or trace an API transaction when diagnostics require it.
You will be working for
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