Description
A student tries to begin a lesson, but the application fails to load. A guide's dashboard displays incorrect mastery scores. L1 support and AI have already attempted resolution without success. The case is now yours — and a child's learning session depends on your ability to identify what went wrong.
The majority of your workload consists of tickets that no one else has been able to resolve, spanning the suite of 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 every piece of information it returns, because an incorrect response delivered to a classroom scales rapidly. You will learn a new product nearly every week. This is the nature of the role, not a caution.
You take full ownership of each issue from start to finish: replicate it, identify the underlying cause, and fix it in the fewest interactions necessary to restore functionality for the student or guide. The analysis you document improves the performance of the next agent and the next AI system, ensuring your solution continues to deliver value well beyond the current ticket. In time, you will become the go-to resource for the team's most difficult education-product challenges.
If you are drawn to complex, undefined problems, and you genuinely care that the product serves a child's education, submit your application.
What you will be doing
- Solve unclear, escalated cases from students, parents, and guides that AI and L1 support were unable to close.
- Replicate issues in an environment that matches the user's device, application, and settings, working with logs and authentic data.
- Research across Alpha's learning applications (tickets, Slack, knowledge repositories, logs) before escalating further.
- Use AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in actual documentation, and validate all output.
- Engage clearly and professionally with non-technical users, collecting sufficient information upfront to resolve cases in one interaction.
- Escalate issues to engineering with comprehensive diagnostic detail when a product defect is confirmed.
- Record your diagnostic process so the next agent, and the next AI system, can leverage it.
What you will NOT be doing
- Working from scripts or flowcharts tied to a single application.
- Managing the simple queue. AI already handles tickets solvable through knowledge-base searches.
- Passing difficult problems to engineering without first replicating and isolating them.
- Allowing AI to substitute for your judgment, or using its responses without verification.
- Waiting for direction, or relying on others to remove obstacles.
Key responsibilities
Diagnose and resolve complex, ambiguous customer problems 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 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.
- 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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