Vim - Technical Support Engineer- AI Native

• Resolve complex issues, build the systems that prevent them • Own Tier 2 support end-to-end: triage, investigate, and resolve complex tickets from account managers and customers; independently or by pulling in Engineering and Product at the right moment. • Own Tier 2 support end-to-end: • Use AI as your primary tool, not a supplement: draft responses, summarize issues, identify ticket patterns, and build intelligent triage workflows that make manual work obsolete. • Use AI as your primary tool, not a supplement: • Run the escalation process: own critical issue escalations across Engineering and Product, keep internal stakeholders informed, and close the loop with customers without waiting to be asked. • Run the escalation process: • Build durable support infrastructure: document SOPs, build automation workflows (Zapier, Make, or similar), and create scalable systems that grow with the product. • Build durable support infrastructure: • Become the internal expert: develop deep knowledge of Vim's platform, features, and internal tooling so you can debug anything without needing a handoff. • Become the internal expert: • Coach Tier 1: review Tier 1 account manager tickets, identify patterns in recurring issues, and build the playbooks that prevent escalation before it happens. • Coach Tier 1: • Close the product feedback loop: synthesize support patterns into signals for Product and Engineering; turning repeated friction into roadmap items. • Close the product feedback loop: • WHAT SUCCESS LOOKS LIKE • Tickets close faster. Issues stop recurring. Providers stay • Resolution time drops because your AI-powered triage and workflows remove the manual steps that slow everything down. • Resolution time drops • Escalations become rarer, not because you're deflecting them; but because the systems you built catch issues before they grow. • Escalations become rarer, • Providers don't churn over support experiences, they stay because issues get resolved clearly, quickly, and without friction. • Providers don't churn over support experiences, • YOU SHOULD APPLY IF • YOU SHOULD APPLY IF • You debug like an engineer and build like a founder • You have three to five years in a technical support or solutions role at a SaaS company; with a track record of closing complex issues independently.AI is already in your daily workflow: you use LLMs, copilots, or AI-powered tools to work faster and smarter; not occasionally, but constantly.You've built support automation: Zapier, Make, or similar; and you know the difference between a workflow that saves one hour and one that scales indefinitely.You're comfortable with technical environments: web application troubleshooting, API behavior, authentication flows, browser-based debugging; you don't need hand-holding to navigate these.You've worked in or around healthcare tech: EHRs, clinical workflows, or payer-provider data flows aren't foreign territory.You've used monitoring and analytics tools: Datadog, Mixpanel, New Relic, or similar; to diagnose issues before users report them. • YOU SHOULD NOT APPLY IF • Be honest with yourself before applying • You treat AI as optional or something to experiment with someday. In this role, AI fluency is table stakes from day one; not a nice-to-have.You prefer reactive support waiting for tickets to arrive instead of building the systems that reduce their volume. We need someone hunting the patterns.You've never written a script, read an API log, or used a monitoring tool in a professional context. The technical floor here is real.You need a manager to assign your priorities. This role requires independent judgment on what to escalate, what to automate, and when to pull in Engineering.