Description
The difficult tickets do not require another person following scripts. They require someone capable of navigating ambiguous environments, misconfigured systems, conflicting evidence, upset customers, and misleading AI outputs—then determining what is genuinely broken. This position is designed for the support engineer drawn to unsolved cases: replicating the failure, analyzing logs, tracking API behavior, examining JSON payloads, distinguishing a 401 from a 404 from a 429, and leveraging AI aggressively without accepting it uncritically.
Most support organizations remain structured around ticket queues, templated responses, escalation chains, and "known issue" documentation. We are constructing the alternative. Routine inquiries are increasingly resolved through AI and L1 processes, meaning human expertise is allocated to the most complex problems. AI is not your substitute here. It is the instrument you control, validate, question, and confirm.
This position is not about copying AI-generated answers, rushing to conclusions, awaiting direction, or escalating the moment the issue becomes unfamiliar. It is not for someone who masters one product then struggles when the next ticket involves a different technology stack. It is about delivering the correct answer in the minimum number of customer interactions the problem permits: reproducing before suggesting solutions, investigating across tickets, Slack threads, knowledge bases, logs, configurations, and actual artifacts before escalating, and composing customer communications clear enough to defuse tension. The technical foundation is assumed: REST APIs, JSON, HTTP status codes, command line, and logs. That establishes baseline competence. Judgment amid uncertainty is what makes you effective.
In this position, your responsibility is to retain ownership of the issue until it is resolved or escalated with clarity, accompanied by diagnostic analysis valuable enough for the next agent and the next AI workflow. You will thrive in this role if the ticket that defies explanation is the one you most want to solve. You will dislike it if you require one product, one process, and external intervention to progress. If that environment energizes you, please apply.
What you will be doing
- AI-Augmented Customer Resolutions: Complex, escalated tickets resolved through deep, practical troubleshooting combined with AI that you guide, anchor in authentic documentation, and validate.
What you will NOT be doing
- Spending two full months onboarding; you will be expected to become productive on multiple products within the first month (we recognize this is demanding)
- Depending on your managers for assistance; if you cannot unblock yourself effectively, you will likely find this role challenging
Key responsibilities
- Combine technical human judgment and AI capabilities to provide exceptional customer support, concentrating on intricate issues that AI cannot yet independently resolve
Candidate requirements
- 2+ years in a hands-on technical position such as technical support, customer support engineering, software engineering, QA, or sysadmin/DevOps. The title does not need to be "support."
- Comfortable constructing 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 (CLI) and logs.
- Hands-on experience using generative AI tools (such as ChatGPT or Claude) in your daily technical work.
- Professional fluency in English, written and spoken.
- Able to work full-time from 1:00 PM – 10:00 PM UTC (8:00 AM – 5:00 PM US Eastern)
Nice to have
- Experience supporting technical or business customers on enterprise software or B2B SaaS, not just internal IT.
- API troubleshooting with tools like Postman or curl.
- A track record of troubleshooting across several unrelated products or tech stacks, not just one.
- Developer-grade depth: you can read code or trace an API call when the problem demands 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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