Description
A student opens the app to begin learning, and nothing loads. A guide checks their dashboard and sees incorrect mastery scores. L1 support and the AI have both attempted a fix and failed. Now the issue is in your hands — and a child's learning session depends on your ability to identify the actual problem.
The majority of your time is spent on 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, review logs and documentation, deploy AI to accelerate the process, and then validate everything it produces — because an incorrect solution delivered to a classroom scales its impact rapidly. You will onboard to a new product nearly every week. This is the nature of the role, not a cautionary note.
You take full ownership of each issue from start to finish: replicate it, identify the underlying cause, and solve it in the fewest interactions necessary to restore functionality for the student or guide. The diagnostic reasoning you document strengthens the capability of the next agent and the next AI system, ensuring your resolution continues to add value well beyond the current ticket. As you progress, you will become the go-to resource for the team's most challenging education-product issues.
If you are drawn to complex, ambiguous challenges, and you genuinely care that the product supports a child's education, submit your application.
What you will be doing
- Resolve complex, escalated support tickets from students, parents, and guides that AI and L1 support were unable to close.
- Replicate failures in an environment that matches the user's device, application, and configuration, leveraging logs and actual artifacts.
- Conduct investigations across Alpha's learning applications (tickets, Slack, knowledge repositories, logs) prior to escalating.
- Guide AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in verified documentation, and validate all output.
- Communicate with clarity and composure to non-technical users, collecting sufficient information upfront to enable single-pass resolution.
- Escalate issues to engineering with complete diagnostic context when a product defect is confirmed.
- Record your diagnostic reasoning to enable reuse by the next agent and future AI workflows.
What you will NOT be doing
- Relying on scripts or decision trees for a single product.
- Working the simple ticket queue. AI already resolves tickets that require only a knowledge-base lookup.
- Escalating difficult problems to engineering without first replicating and isolating them.
- Allowing AI to do your thinking, or copying its output without verification.
- Waiting for direction, or for someone else to remove blockers.
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
Applying for a role? Here’s what to expect.
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