Description
A student opens the app and nothing loads. A guide's dashboard displays incorrect mastery data. L1 support and the AI workflow have both tried and failed. The issue is now yours — and a child's learning session depends on you discovering what went wrong.
The majority of your time is spent on tickets that no one else has been able to resolve, spanning the full range of applications that comprise Alpha's learning platform. You recreate the issue in an environment matching the student's or guide's configuration, review logs and documentation, deploy AI to accelerate the process, then validate all outputs — because an incorrect response delivered to a classroom scales the problem fast. Ramping up on a new product nearly every week is a core part of the role, not an exception.
You take full ownership of each issue from start to finish: recreate it, identify the underlying cause, and resolve it with the minimum number of interactions needed to restore functionality for the student or guide. The diagnostic reasoning you capture improves both the next agent's effectiveness and future AI workflows, ensuring your solution continues to add value well beyond the current ticket. Over time, you establish yourself as the go-to resource for the team's most challenging education-product issues.
If you seek complex, undefined problems and genuinely care that the product you support enables a child to learn, you should apply.
What you will be doing
- Resolve complex, escalated tickets from students, parents, and guides that neither AI nor L1 support were able to close.
- Recreate failures in an environment that replicates the user's device, application, and settings, relying on logs and actual artifacts.
- Conduct investigations across Alpha's learning applications (ticketing systems, Slack channels, knowledge repositories, logs) prior to escalation.
- Use AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in verified documentation, and validate every result.
- Interact clearly and professionally with non-technical users, collecting sufficient information upfront to resolve issues in one exchange.
- Escalate to engineering with comprehensive diagnostic context when a product defect is confirmed.
- Record your diagnostic process so subsequent agents and AI workflows can leverage it.
What you will NOT be doing
- Working from scripts or decision trees for a single application.
- Processing the simple queue. AI already resolves tickets that require only knowledge-base lookups.
- Passing difficult problems to engineering without first recreating and isolating them.
- Allowing AI to perform the analysis for you, or using its output without verification.
- Waiting for direction or relying on others to remove obstacles.
Key responsibilities
Resolve ambiguous, technically complex customer issues to root cause across Alpha's education products.
Candidate requirements
- 2+ years in a hands-on technical role such as technical support, software engineering, QA, sysadmin, or DevOps. The job title does not need to be "support."
- Comfortable constructing and interpreting REST API calls and JSON, understanding HTTP status codes (such as 401 vs 404 and 429 vs 403), and operating in a command line and log environment.
- Practical experience using AI tools (such as ChatGPT or Claude) as part of your regular technical workflow.
- Professional fluency in English, both written and spoken.
- Available to work full-time (40 hours/week), with all working hours falling between 1:00 PM – 10:00 PM UTC (8:00 AM – 5:00 PM US Eastern).
Nice to have
- Experience supporting non-technical end users (in education, edtech, or consumer applications), not exclusively IT professionals.
- Practical experience guiding AI tools and identifying their errors.
- A history of troubleshooting across multiple unrelated products, rather than focusing on one.
- Developer-level proficiency: capable of reading code or tracing an API call when the situation requires it.
You will be working for
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