Description
A student opens the app to begin their lesson and nothing loads. A guide checks their dashboard and sees incorrect mastery scores. L1 support and the AI assistant have both attempted to resolve the issue and failed. Now the problem is yours—and a child's learning session depends on you identifying what went wrong.
The majority of your time will be spent on tickets that no one else has been able to resolve, spanning the multiple applications that comprise Alpha's learning platform. You will recreate the issue in an environment matching the student's or guide's configuration, examine logs and documentation, leverage AI to accelerate your process, and then validate all outputs—because an incorrect response delivered to a classroom can escalate rapidly. Ramping up on a different product nearly every week is expected. That defines the role, not a cautionary note.
You take full ownership of each issue: replicate it, identify the underlying cause, and fix it with minimal back-and-forth to restore functionality for the student or guide. The diagnostic reasoning you document strengthens the capabilities of the next support agent and the next AI system, ensuring your solution 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 difficult, unclear problems, and you genuinely care that the product ultimately supports a child's education, we encourage you to apply.
What you will be doing
- Resolve unclear, escalated issues from students, parents, and guides that neither AI nor L1 support successfully closed.
- Replicate failures in an environment that matches the user's device, application, and settings, using logs and actual data.
- Investigate across Alpha's suite of learning applications (tickets, Slack, knowledge repositories, logs) prior to escalation.
- Use AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in authentic documentation, and validate all results.
- Communicate with clarity and composure to non-technical users, collecting sufficient information upfront to resolve issues in one interaction.
- Escalate issues to engineering with complete diagnostic context when a product defect is confirmed.
- Document your diagnostic process so future agents and AI workflows can build on it.
What you will NOT be doing
- Following scripts or decision trees for a single product.
- Working the simple queue. AI already resolves tickets that require only a knowledge-base reference.
- Escalating difficult problems to engineering before reproducing and narrowing them yourself.
- Allowing AI to do the thinking for you, or copying its responses without verification.
- Waiting for direction, or depending on others 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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