Description
The toughest support cases don't require another person following scripts. They require someone capable of navigating unclear situations, misconfigured systems, conflicting evidence, upset customers, and AI-generated false leads—then determining what's truly broken. This position is designed for the support engineer drawn to the unresolved ticket: replicating the error, examining logs, mapping API behavior, analyzing JSON payloads, distinguishing a 401 from a 404 from a 429, and leveraging AI aggressively without placing blind trust in it.
Most support organizations still operate using queues, macros, escalation chains, and "known issue" documentation. We are constructing something fundamentally different. Standard support requests are increasingly managed through AI and L1 processes, meaning human analysis is preserved for the hardest challenges. AI isn't replacing you in this role. It's the instrument you direct, validate, question, and confirm.
This position is not about copying AI-generated responses, making rapid guesses, awaiting directions, or escalating the instant an issue becomes unfamiliar. It isn't suited for someone who masters one product but stalls when the following ticket involves a different technology stack. It's about delivering the correct solution in the minimum number of customer interactions the situation permits: replicating before suggesting remedies, investigating across tickets, Slack channels, knowledge bases, logs, configurations, and actual evidence before escalating, and composing customer replies clear enough to defuse tension. The technical foundation is assumed: REST APIs, JSON, HTTP status codes, command line interfaces, and logs. That provides entry. Sound judgment amid uncertainty is what makes you effective.
In this position, your responsibility is to retain ownership of each issue until resolution or clean handoff, with diagnostic logic valuable enough for the subsequent agent and future AI workflows. You'll thrive in this role if the ticket that resists explanation is precisely the one you want most. You'll dislike it if you require a single product, a single playbook, and external help to move forward. If that type of challenge energizes you, we encourage you to apply.
What you will be doing
- AI-Augmented Customer Resolutions: Resolve ambiguous, escalated tickets by integrating thorough, hands-on investigation with AI tools that you guide, anchor in verified documentation, and cross-check.
What you will NOT be doing
- Spending two full months onboarding; you will need to become productive across multiple products within your first month (we recognize this expectation is demanding)
- Depending on managers for assistance; if you are not skilled at self-unblocking, this role will present significant difficulties
Key responsibilities
- Combine deep technical human judgment with AI-powered tools to provide outstanding customer support, concentrating on sophisticated problems that AI cannot yet independently solve
Candidate requirements
- 2+ years in a hands-on technical position including technical support, customer support engineering, software engineering, QA, or sysadmin/DevOps. The job title does not need to say "support."
- Proficient in constructing and interpreting REST API calls and JSON, understanding HTTP status codes (such as 401 vs 404 and 429 vs 403), and operating within command line interfaces (CLI) and log files.
- Practical experience applying generative AI tools (such as ChatGPT or Claude) within your regular technical workflow.
- Professional-level fluency in English, 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 customers using enterprise software or B2B SaaS, beyond internal IT environments.
- API debugging experience using tools like Postman or curl.
- Demonstrated history of troubleshooting across multiple unrelated products or technology stacks, not limited to a single domain.
- Developer-level competency: capable of reading code or tracing API transactions 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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