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Service Delivery and Support Manager
Full-time
About AirportLabs
AirportLabs provides a complete suite of products that drive efficiency in aviation. Our products and solutions help major airports, airlines, and ground handlers worldwide solve the hardest operational problems.
The Role
This is an AI-first operations role. You will govern a model where AI handles the majority of support volume: T0 (chatbot, auto-triage, self-service) and T1 (auto-resolution for known patterns, AI-suggested responses), targeting 50–60% combined deflection. The knowledge base is AI-maintained. Incident triage for known issues is AI-automated. Operational analytics are AI-driven.
Your human contribution is what AI cannot do: governing AI quality, designing the AI-human handoff boundary, managing complex escalations that require judgment and customer relationship context, and continuously expanding the frontier of what AI can resolve.
You will lead two Leads: Lead AI Operations and Knowledge (who owns the AI engine) and Lead Support and Escalation (who owns T2+ human support).
Responsibilities
Govern the AI-human hybrid support model: design and maintain the boundary between AI-automated and human-handled work — escalation triggers, AI confidence thresholds, handoff protocols
Manage the continuous AI training loop: ensure human T2+ resolutions are systematically fed back into AI models
Own the AI-maintained knowledge base: AI auto-generates articles from ticket resolutions, implementation docs, and release notes
Own configuration-as-knowledge: ensure customer configurations are auto-documented and queryable
Oversee T2+ human support and incident coordination for complex issues requiring judgment
Drive operational improvement through AI-powered process mining, trend detection, and analytics
Qualifications
5+ years in service delivery, support management, or operations, with at least 2 years managing teams in SaaS
Proven experience with AI-powered support tools: chatbots, auto-triage, AI-suggested responses, AI knowledge management
Experience managing the human-AI boundary: escalation triggers, AI quality monitoring, feedback loops
Data-driven: comfortable interpreting support metrics, CSAT data, and operational analytics
Experience with knowledge management at scale
Fluency in Romanian is mandatory for internal collaboration
