Description
The education support ecosystem is drowning in complexity while expectations from schools, students, and families continue to rise. Schools now expect instant, AI-assisted answers across learning platforms, SIS systems, devices, and workflows. However, most organizations are stuck in fragmented tooling, manual escalations, and brittle processes that fail under real-world conditions.
We close this gap with a fundamentally different model: AI-augmented “cyborg” agents operating at the center of a live educational ecosystem. In this role, you will shape how the system learns. Every fix improves future automations, every root cause analysis informs process and policy, and every edge case you unravel strengthens outcomes for thousands of students and educators.
This is hands-on, production-depth problem solving in a service environment. You will dissect ambiguous, multi-stakeholder failures across learning applications, SIS platforms, identity systems, networks, and operational workflows; leverage AI to hypothesize, test, and accelerate resolution paths; document the human reasoning that teaches both systems and teams; and proactively identify patterns that turn one-off interventions into durable, cross-functional improvements.
This is not ticket triage, script-following, or “escalate and wait.” If you thrive when documentation is incomplete, when problems span engineering, operations, and academics, and when you can move from technical debugging to stakeholder alignment without losing rigor, then this role will feel like home.
What you will be doing
- AI-Augmented Customer Resolutions: Analyze complex tickets escalated by AI systems, apply human expertise to areas where AI falls short, and then close the gap by improving the AI system
What you will NOT be doing
- Taking two whole months to get up to speed; you will be expected to ramp up one several products within the first month (we are aware this is aggressive)
- Relying on your managers for help; if you are not adept at unblocking yourself, you will likely struggle in this role
Key responsibilities
- Integrate technical human expertise and AI capabilities to deliver exceptional customer support, focusing on complex issues that AI cannot yet fully resolve
Candidate requirements
- Must be based in North or South America
- At least 3 total years of experience in a technical customer support role
- Basic coding skills for the purpose of troubleshooting/bug fixes
- Advanced generative AI proficiency (i.e., use of multiple AI tools, ability to automate workflows and custom GPTs); if you've only used LLMs for research, learning, brainstorming, or content generation, that will be deemed insufficient
- Troubleshooting Skills: Explaining complex issues in simple terms, demonstrating strong problem understanding, recommending relevant troubleshooting strategies, proposing multiple solution paths, and showing attention to detail
You will be working for
Applying for a role? Here’s what to expect.
Crossover's skill assessment process combines innovative AI power with decades of human research, to take the guesswork, human bias, and pointless filters out of recruiting high-performing teams.
Chat-style screening interview.
Cognitive aptitude test.
Prove real-world job skills.
Interview with the hiring manager.
Accept job offer.
Pass proctored test.
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