Head of Technical Support, Mintlify

• 4+ years in technical support, support engineering, or a similar customer-facing technical role, including 1+ years managing a team
• Experience leading support at a high-growth developer-tools or developer-focused company
• Strong fluency in docs and developer tooling: Git and GitHub workflows, CI/CD, Markdown/MDX, static sites, APIs and OpenAPI specs, DNS and hosting
• Hands-on debugging skills: you can reproduce an issue, read logs and config, and explain the root cause to an engineer or a customer
• You've deployed AI in a support org (agents, deflection, or AI-assisted workflows) and can show what it changed in the numbers
• Operational rigor: you've defined SLAs, built dashboards, reported metrics to leadership, and forecast volume and headcount
• Calm, clear communication with enterprise customers during escalations and incidents
• Able to work from our San Francisco office 5 days a week

Desirable

• We're hiring a Head of Technical Support to own how Mintlify supports its customers, from fast-growing startups to our largest enterprise accounts
• You'll lead a growing team of support engineers and stay hands-on: working the hardest escalations, debugging customer setups, and building the tooling that lets the team scale
• Enterprise comes first
• As more large companies run their documentation on Mintlify, they expect clear SLAs, fast escalation paths, and a support partner who can go deep technically
• You'll build that motion, raise the operational bar with real metrics, and use AI so support keeps pace as our customer base grows
• Define and run tiered SLAs, priority levels, and escalation paths for enterprise customers
• Own critical escalations end-to-end, including communication with customer engineering leaders and executives
• Partner with Sales, Solutions, and Customer Success on onboarding, renewals, and at-risk accounts
• Handle technical questions in security reviews and complex setups such as SSO, custom domains, and CI/CD integrations
• Deploy and tune AI agents that deflect and resolve common questions, and measure their real resolution rate
• Build internal tools, scripts, and workflows that cut handle time and repeat work
• Turn recurring tickets into docs, product fixes, or automations
• Own bug triage: clear reproductions, severity, and routing to the right team
• Bring ticket data into roadmap discussions so the most painful issues get fixed
• Run incident communication with customers alongside Engineering
• Set up the metrics that matter (first response, time to resolution, CSAT, backlog, escalation rate, AI resolution rate) and report on them weekly
• Forecast volume and headcount as the customer base grows
• Hire, coach, and level support engineers; build career paths and a QA process
• Set coverage and on-call so enterprise SLAs hold
• 30 days: You've worked tickets and escalations yourself, met the team and key enterprise customers, and have a baseline of current support metrics
• 90 days: Enterprise SLAs and escalation paths are defined and live, a weekly metrics review is running, and you've shared a plan for AI deflection and team growth
• 6 months: Enterprise SLAs are met consistently, AI resolves a measured and growing share of inbound volume, and bug triage with Engineering runs on a clear cadence
• 12 months: Support scales with the customer base, the team has clear levels and career paths, and support data shapes the roadmap