Service Delivery and Support Manager

About the role

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, improve efficiency, and develop the value of their services.

We are looking for a Manager Service Delivery and Support to lead our operations function — someone who can govern an AI-human hybrid support model, drive AI automation coverage, and ensure every customer receives fast, reliable, and intelligent support across all 10 of our SaaS products.

AirportLabs serves airport operators, airlines, and ground handlers across multiple geographies. Our customers operate 24/7 in high-stakes environments where system downtime has direct operational impact — delayed flights, misallocated gates, broken passenger flows. Support quality is not a back-office concern; it is a competitive differentiator and a retention driver. Your job is to make sure the operations function delivers at this standard — and scales through AI rather than headcount.

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 — dashboards, trend detection, process mining — 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 — T0\+T1 support, KB automation, incident automation, operational analytics) and Lead Support and Escalation (who owns T2\+ human support and novel incident coordination). You are accountable for both channels: AI quality and human quality.

If you are an operations leader who thinks in systems, is energised by AI-powered automation, and wants to build the support model for a growing SaaS company in aviation, we'd love to meet you.

Key data for you to consider

• Yearly profit share

• Various performance and behaviour-based bonuses

• In-office or hybrid (partial office \& partial remote)

• Office location: Cluj-Napoca

• Contract based on PFA or SRL with our UK entity

• Paid holidays

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, and AI quality governance.

• Manage the continuous AI training loop: ensure human T2\+ resolutions are systematically captured, reviewed, and fed back into AI models to expand AI resolution coverage over time.

• Own the AI-maintained knowledge base: AI auto-generates articles from ticket resolutions, implementation documentation, and product release notes. You govern quality, freshness, and coverage.

• Own configuration-as-knowledge: ensure customer configurations are auto-documented during implementation and maintained as queryable records, so support can answer "how is this configured for customer X" without escalating to product teams.

• Own customer document automation: AI auto-generates standard certificates, forms, and vendor questionnaire responses from company data. Non-standard requests are routed to the appropriate internal owner with pre-populated context.

• Oversee T2\+ human support and incident coordination: complex issues, novel incidents, and customer escalations that require judgment, customer relationship context, and cross-functional coordination.

• Drive operational improvement through AI-powered process mining, trend detection, and analytics. Monitor cost per ticket, AI deflection rate, SLA adherence, and CSAT — and take action when metrics move in the wrong direction.

• Coordinate cross-functionally with Technology (AI tooling), PMO (implementation handover), Product teams (support insights feeding roadmaps), Customer Success (at-risk accounts), Security (incident coordination), and SRE (observability data feeding AI).

Qualifications \& Skills

• 5\+ years in service delivery, support management, or operations, with at least 2 years managing teams in a SaaS or technology company.

• Proven experience with AI-powered support tools: chatbots, auto-triage, AI-suggested responses, and AI knowledge management. Comfortable configuring, governing, and measuring AI tool effectiveness — not just using them passively.

• Strong understanding of tiered support models (T0–T3\), SLA management, and incident management processes.

• Experience managing the human-AI boundary: defining escalation triggers, monitoring AI quality (false positives, false negatives, CSAT divergence), and designing feedback loops that improve AI over time.

• Data-driven: comfortable interpreting support metrics, CSAT data, and operational analytics to make decisions and justify investments.

• Experience with knowledge management at scale: KB structure, content lifecycle, freshness governance, and quality assurance.

• Coaching ability: can develop two Leads with very different profiles (one AI/technical, one human/relational) without micro-managing.

• Cross-functional coordination skills: ability to work effectively with Technology, Product, PMO, and Commercial teams — support does not exist in isolation.

• Excellent communication in English. Fluency in Romanian is mandatory for internal collaboration.

• Bachelor's degree or higher.

Nice to have

• Familiarity with ITIL or similar service management frameworks, adapted for modern SaaS (not waterfall-era rigidity)

• Experience with knowledge automation: AI-generated content governance, auto-publishing workflows, freshness monitoring

• Experience designing follow-the-sun or geographically distributed support models

• Familiarity with observability tools (Datadog, PagerDuty, Grafana, or similar) and how they integrate with support and incident management

• Experience with customer-facing documentation processes (certificates, compliance questionnaires, vendor forms)

• Aviation, airport, or transportation domain experience

• Experience with Team Topologies or cognitive load management principles

Our recruitment process

We will use a three-step process for the recruitment of this role:

1. A first questionnaire on support operations fundamentals, AI-powered operations, and structured thinking with the candidates who have been selected based on the CV \& motivation description.

2. A first interview with the candidates who have been selected based on the questionnaire, where we will discuss your operations experience, your approach to AI-powered support, and how you think about the AI-human boundary.

3. A practical exercise will be sent over email to the candidates selected: you will receive a realistic support operations scenario and be expected to analyse data, design improvements, and handle an operational situation within 4 working days, then present your approach and output.

Career development

Should you be interested in further professional development, we will support you to boost your skills and capabilities. Being a product company, we have a wider breadth of departments and skills that may be attractive to you:

• Head of Operations

• Product Management

• Programme Management

• Customer Success

• Top Management

We place efficiency at the core of our business. Our day-to-day efforts contribute to improving the quality of passengers' travel experience all across the world.

We foster a values-driven culture; therefore, it is essential that colleagues who join our team abide by and uphold our company values: Assertiveness, Efficiency, Grit, Initiative, Kindness \& Collaboration, Knowledge transfer, Openness, Ownership, Responsibility \& Accountability, Predictability, Psychological safety, and Transparency.