Description
A student tries to start a lesson and the application fails to load. A guide opens their dashboard and sees incorrect mastery scores. L1 support and the AI have both attempted resolution without success. The issue is now yours — and a child's learning session depends on you identifying the actual problem.
The majority of your day 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, examine logs and documentation, leverage AI to accelerate your work, and then validate all of its output, because an incorrect response deployed in a classroom creates cascading problems. You will onboard to a new product nearly every week. This is the nature of the role, not a caution.
You take complete ownership of each issue: replicate it, identify the underlying cause, and resolve it with the minimum number of interactions required to restore functionality for the student or guide. The diagnostic reasoning you document improves the capability of the next agent and the next AI workflow, ensuring your solution continues to deliver value well after you have moved on to another ticket. With time, you become the individual the team relies on for its most challenging education-product issues.
If you are drawn to difficult, ambiguous problems, and you genuinely care that the product ultimately 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 was able to close.
- Replicate failures in an environment that matches the user's device, application, and configuration, working from logs and actual artifacts.
- Conduct investigation across Alpha's learning applications (tickets, Slack, knowledge bases, logs) prior to escalating.
- Deploy AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in real documentation, and validate each 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 is genuinely defective.
- Record your diagnostic reasoning so the next person, and the next AI workflow, can leverage it.
What you will NOT be doing
- Working from scripts or decision trees on a single product.
- Processing the simple queue. AI already resolves the tickets that a knowledge-base search can address.
- Passing difficult problems to engineering without first replicating and isolating them.
- Allowing AI to think for you, or inserting its output without verification.
- Waiting to receive instructions, 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
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