Enterprise Customer Support Engineer

Vapi•San Francisco, CA

About The Position

We’re creating the shift to voice as humanity’s default interface. We’re the most configurable platform for deploying voice agents. We’re grown to 400,000 developers in 20 months, adding 2,000+ every day. As enterprise adoption grows, we need fast, technically credible frontline support to protect uptime and customer trust. ● Enterprise customers are deploying complex voice AI systems in production environments where speed and precision matter. ● This role ensures issues are triaged, resolved, or escalated cleanly within SLA while strengthening our support infrastructure over time.

Requirements

4+ years in technical support, support engineering, or customer-facing technical roles at a SaaS or API-first company.
Strong troubleshooting ability with REST APIs, JSON payloads, webhooks, and configuration debugging.
Comfortable reading API error responses, tracing webhook flows, and diagnosing issues without writing production code.
Experience managing SLA-bound queues in systems like Zendesk, Intercom, or Jira Service Management.
Clear communicator who can explain technical root causes to customers without unnecessary jargon.
Highly organized with strong documentation habits and thorough ticket hygiene.
Comfortable in fast-paced environments where enterprise production systems are at stake.

Nice To Haves

Experience with voice/telephony systems (SIP, WebRTC, Twilio, Vonage), AI agents, LLMs, or basic scripting for debugging.

Responsibilities

Learn Vapi’s API surface area, common integration patterns, and production deployment workflows.
Shadow ticket triage and begin resolving straightforward L1 issues independently.
Understand tiering framework (P0, P1, P2) and SLA expectations.
Familiarize yourself with documentation gaps and internal runbooks.
Own front-line enterprise ticket triage with a focus on resolving most tickets within 30 minutes.
Apply severity-based prioritization and escalate cleanly when required with full reproduction context.
Partner with Deployment Strategists to identify recurring issues and customer health risks.
Begin contributing to internal knowledge base and runbooks.
Achieve strong L1 resolution rate (70%+) with consistent SLA adherence.
Actively improve support workflows, automation triggers, and routing logic.
Contribute to SLA automation initiatives (Tasker, Slack bots, routing improvements).
Strengthen documentation to reduce repeat issues and increase team velocity.