Description
The toughest tickets don't require another script-reader. They demand someone capable of stepping into unclear situations, misconfigured systems, conflicting evidence, upset customers, and AI-produced false leads—then determining what's genuinely broken. This position is designed for the support engineer drawn to unresolved cases: replicating the error, analyzing logs, examining API patterns, inspecting JSON data, distinguishing a 401 from a 404 from a 429, and leveraging AI aggressively without accepting it uncritically.
Traditional support organizations remain structured around ticket queues, templated responses, handoff protocols, and documented issue libraries. We're constructing something fundamentally different. Routine inquiries are increasingly managed through AI and first-tier processes, meaning human expertise is deployed only for the hardest challenges. AI isn't here to replace you. It's the instrument you guide, validate, question, and confirm.
This position isn't about copying AI-generated solutions, making rapid guesses, awaiting direction, or escalating the instant an issue becomes unfamiliar. It's not suited for someone who masters one product but stalls when the following ticket involves a different technology. It's about delivering the correct resolution with the minimum customer interactions the situation permits: reproducing issues before proposing fixes, researching across tickets, Slack channels, knowledge bases, logs, configurations, and actual evidence before escalating, and composing customer communications precise enough to defuse tension. The technical foundation is assumed: REST APIs, JSON, HTTP response codes, command-line tools, and log analysis. That provides entry. Sound judgment amid uncertainty is what makes you effective.
In this capacity, you own each issue until resolution or clean escalation, with diagnostic logic valuable enough for subsequent agents and future AI processes. You'll thrive in this role if the ticket that defies explanation is precisely what you pursue. You'll dislike it if you require one product, one procedure, and external help to move forward. If such conditions focus your abilities, submit your application.
What you will be doing
- AI-Augmented Customer Resolutions: Complex, escalated tickets addressed through deep, practical troubleshooting combined with AI that you control, anchor in verified documentation, and validate.
What you will NOT be doing
- Spending two full months to reach productivity; you'll be required to become operational on multiple products within your first month (we recognize this expectation is demanding)
- Depending on managers for assistance; if you're not skilled at removing your own blockers, this role will prove difficult
Key responsibilities
- Combine technical human judgment and AI tools to provide outstanding customer support, concentrating on complicated issues that AI cannot yet independently resolve
Candidate requirements
- 2+ years in a technical, hands-on position such as technical support, customer support engineering, software engineering, QA, or sysadmin/DevOps. Your job title doesn't have to say "support."
- Comfortable constructing and interpreting REST API requests and JSON, understanding HTTP status codes (such as 401 vs 404 and 429 vs 403), and operating within command-line interfaces (CLI) and logs.
- Practical experience applying generative AI tools (such as ChatGPT or Claude) in everyday technical tasks.
- Professional-level English proficiency, both written and verbal.
- Available to work full-time from 1:00 PM – 10:00 PM UTC (8:00 AM – 5:00 PM US Eastern)
Nice to have
- Background supporting technical or business clients on enterprise software or B2B SaaS, beyond internal IT only.
- API diagnosis using tools like Postman or curl.
- Demonstrated ability troubleshooting multiple unrelated products or technology stacks, not simply one.
- Developer-level proficiency: capable of reading code or tracing API interactions when the situation requires it.
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.
Pass proctored test.
Accept job offer.
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