Description
A student attempts to begin a lesson, but the app refuses to load. A guide's dashboard displays incorrect mastery scores. L1 support and the AI have both attempted resolution without success. The issue now falls to you — and a child's educational session depends on your ability to identify the actual problem.
The majority of your time is dedicated to tickets that no one else has been able to resolve, spanning the multiple applications that comprise Alpha's learning platform. You replicate the issue in an environment matching the student's or guide's configuration, examine logs and documentation, leverage AI to accelerate your work, and then validate everything it produces, because an incorrect solution delivered to a classroom can cascade rapidly. You will onboard to a different product nearly every week. This is the nature of the role, not a cautionary note.
You take full ownership of each issue: replicate it, identify the underlying cause, and resolve it with minimal back-and-forth to restore functionality for the student or guide. The documentation you create enables the next agent and the next AI workflow to operate more effectively, ensuring your solution continues to deliver value well after you've moved to the next ticket. In time, you become the go-to resource for the team's most challenging education-product issues.
If you are drawn to difficult, undefined problems, and you genuinely care that the product ultimately supports a child's learning, apply.
What you will be doing
- Resolve escalated, ambiguous tickets from students, parents, and guides that neither AI nor L1 support was able to close.
- Replicate failures in an environment matching the user's device, application, and configuration, drawing on logs and actual artifacts.
- Research across Alpha's learning applications (tickets, Slack, knowledge bases, logs) prior to escalation.
- Use AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in authentic documentation, and validate all output.
- Engage clearly and professionally with non-technical users, collecting sufficient detail upfront to enable single-pass resolution.
- Escalate issues to engineering with complete diagnostic context when a product defect is confirmed.
- Record your diagnostic reasoning so subsequent agents and AI workflows can leverage it.
What you will NOT be doing
- Working from scripts or decision trees tied to a single product.
- Servicing the simple queue. AI already resolves tickets that require only knowledge-base lookups.
- Escalating difficult problems to engineering without first replicating and isolating them.
- Allowing AI to substitute for your judgment, or submitting its output unchecked.
- Waiting for direction, or depending on others to clear obstacles for you.
Key responsibilities
Resolve complex, ambiguous 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 title does not need to be "support."
- Comfortable making and reading REST API calls and JSON, interpreting HTTP status codes (such as 401 vs 404 and 429 vs 403), and working in a command line and logs.
- Hands-on experience using AI tools (such as ChatGPT or Claude) in your daily technical work.
- Professional fluency in English, 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 apps), not just IT professionals.
- Hands-on experience directing AI tools and catching their mistakes.
- A track record of troubleshooting across several unrelated products, not just one.
- Developer-grade depth: you can read code or trace an API call when the problem demands it.
You will be working for
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