Description
A student begins their lesson, but the app refuses to load. A guide's dashboard displays incorrect mastery scores. L1 and the AI have both attempted to resolve the issue and failed. The problem is now yours—and a child's learning session depends on your ability to identify what has actually gone wrong.
The majority of your time is spent on tickets that others could not resolve, spanning the various applications that constitute Alpha's learning platform. You replicate the failure in an environment matching the student's or guide's configuration, examine logs and documentation, leverage AI to accelerate your work, and then validate everything it produces—because an incorrect answer 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 hold accountability for each problem from start to finish: replicate it, identify the root cause, and resolve it with the fewest interactions necessary to restore functionality for the student or guide. The 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 proceed to the next ticket. With time, you will become the person 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, apply.
What you will be doing
- Resolve complex, escalated tickets from students, parents, and guides that neither AI nor L1 support could close.
- Replicate failures in an environment mirroring the user's device, app, and configuration, working with logs and actual artifacts.
- Investigate across Alpha's learning apps (tickets, Slack, knowledge bases, logs) prior to escalation.
- Use AI tools (such as ChatGPT or Claude) to accelerate diagnosis, anchor them in authentic documentation, and validate each output.
- Communicate clearly and professionally with non-technical users, collecting sufficient information upfront to resolve issues in a single interaction.
- Escalate issues to engineering with complete diagnostic context when a product is truly defective.
- Document your diagnostic reasoning so the next person, and the next AI workflow, can apply it.
What you will NOT be doing
- Following scripts or decision trees for a single product.
- Working the easy queue. AI already resolves the tickets that can be solved with a knowledge-base lookup.
- Escalating difficult problems to engineering without first replicating and isolating them.
- Allowing AI to think for you, or copying its output without verification.
- Waiting to be directed, or for 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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Prove real-world job skills.
Interview with the hiring manager.
Pass proctored test.
Accept job offer.
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