Description
A student attempts to begin their lesson, and the application fails to load. A guide's dashboard displays incorrect mastery scores. L1 support and AI have already attempted resolution without success. The issue is now yours to solve — and a child's learning session depends on your ability to identify what has actually gone wrong.
The majority of your workday is spent on tickets that no one else has been able to close, spanning the numerous applications that comprise Alpha's learning platform. You recreate the failure in an environment that replicates the student's or guide's configuration, examine logs and documentation, deploy AI to accelerate your work, and then validate everything it provides, because an incorrect answer delivered to a classroom can escalate 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: reproduce it, identify the root cause, and resolve it with the fewest interactions necessary to restore functionality for the student or guide. The documentation you create strengthens the next agent and the next AI workflow, ensuring your solution continues to deliver value long after you proceed to the next ticket. Over time, you emerge as the team member others turn to for the most challenging education-product issues.
If you seek the difficult, ambiguous problem, and you genuinely care that the product on the other end supports a child's learning, submit your application.
What you will be doing
- Resolve complex, escalated tickets from students, parents, and guides that neither AI nor L1 support succeeded in closing.
- Recreate 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 bases, logs) prior to escalation.
- Leverage AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in authentic documentation, and validate every result.
- Communicate with clarity and composure to non-technical users, collecting sufficient information upfront to resolve issues in a single interaction.
- Escalate issues to engineering with comprehensive diagnostic context when a product defect is confirmed.
- Record your diagnostic reasoning so subsequent agents, and future AI workflows, can apply it.
What you will NOT be doing
- Executing scripts or decision trees on a single product.
- Managing the easy queue. AI already resolves tickets that require only a knowledge-base lookup.
- Escalating difficult problems to engineering without first reproducing and isolating them.
- Allowing AI to perform the thinking for you, or copying its output without verification.
- Waiting for instructions, or for someone else to remove obstacles.
Key responsibilities
Diagnose and 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 job title does not need to be "support."
- Proficient in 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 logs.
- Practical 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 providing support to non-technical end users (in education, edtech, or consumer apps), not solely IT professionals.
- Practical experience guiding AI tools and identifying their errors.
- A history of troubleshooting across multiple unrelated products, not just one.
- Developer-level proficiency: you can interpret code or trace an API call when the situation requires it.
You will be working for
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