Description

The hard tickets do not need another script follower. They need someone who can walk into ambiguous context, broken configs, contradictory clues, frustrated customers, and AI-generated dead ends, then figure out what is actually wrong. This role is for the support engineer who likes the unsolved case: reproducing the failure, reading the logs, tracing API behavior, interrogating JSON payloads, separating a 401 from a 404 from a 429, and pushing AI hard without trusting it blindly.

Most support teams are still built around queues, macros, handoffs, and “known issue” playbooks. We are building the opposite. Routine support is increasingly handled by AI and L1 workflows, which means human judgment is reserved for the most difficult problems. AI is not your replacement here. It is the tool you direct, ground, challenge, and verify.

This job is not about pasting AI answers, guessing fast, waiting for instructions, or escalating the moment the issue stops looking familiar. It is not for someone who goes deep on one product and freezes when the next ticket lives in a different stack. It is about getting the answer right in the fewest customer touches the problem allows: reproducing before recommending action, investigating across tickets, Slack, KBs, logs, configs, and real artifacts before escalating, and writing customer responses clear enough to de-escalate the situation. The technical baseline is expected: REST APIs, JSON, HTTP status codes, command line, and logs. That gets you in the door. Judgment under ambiguity is what makes you dangerous.

In this role, your job is to own the issue until it is resolved or elevated cleanly, with diagnostic reasoning useful enough for the next agent and the next AI workflow. You will love this role if the ticket that refuses to make sense is the one you want most. You will hate it if you need one product, one playbook, and someone else to unblock you. If that kind of pressure sharpens you, please apply.

What you will be doing

AI-Augmented Customer Resolutions: Ambiguous, escalated tickets resolved by combining deep, hands-on troubleshooting with AI that you direct, ground in real documentation, and verify.

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

2+ years in a hands-on technical role such as technical support, customer support engineering, software engineering, QA, or sysadmin/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 (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.