Etihad Airways — the UAE’s national airline and one of the world’s most admired aviation brands — is hiring a technically sharp, hands-on Conversational AI Service Manager in Abu Dhabi to own the daily operational performance, accuracy, and continuous improvement of its conversational AI bots across Chat, IVR, WhatsApp, Webchat, and Social channels. This is a precision analytical role — reviewing daily passenger conversations, eliminating AI hallucinations and logic loops, fine-tuning NLU models, optimizing bot resolution rates, and ensuring fact-accurate passenger self-service — at one of the world’s most technologically ambitious airlines, as it executes its Journey 2030 vision to double its fleet and reshape global aviation.
About Etihad Airways — Shaping the Future of Global Aviation
Company: Etihad Airways — UAE National Airline | Hub: Abu Dhabi International Airport
Vision: Journey 2030 — doubling the fleet, expanding the network, growing talent for a new era of excellence
Channels: Chat · IVR voice bots · WhatsApp · Webchat · Social messaging platforms
AI Focus: GenAI / LLM-driven passenger self-service · Bot resolution optimization · NLU model accuracy
Mission: Connecting people across continents and cultures — making the world your workplace
Why This Etihad Conversational AI Role in Abu Dhabi Is a Career-Defining Opportunity
Aviation AI Leadership: Own the operational performance of AI bots serving millions of Etihad passengers globally — genuinely consequential work
GenAI at Scale: Monitor and eliminate LLM hallucinations in real time on live, production conversational AI serving real airline passengers
Journey 2030: Join Etihad during one of the most ambitious airline growth programs in the world — be part of a transformational organizational moment
Tax-Free Abu Dhabi: Highly competitive AI management salary — zero personal income tax in the UAE
Position Overview
This Conversational AI Service Manager role at Etihad Airways in Abu Dhabi is a uniquely analytical and operationally demanding position responsible for the daily health, accuracy, and performance of Etihad’s conversational AI across all passenger-facing digital channels. Every day, you will review actual passenger conversation transcripts, hunt and eliminate AI hallucinations and factual inaccuracies in GenAI and LLM-driven responses, re-classify unhandled intents, add NLU training phrases, optimize bot logic and intent mappings, validate knowledge base accuracy for airline policies, test prompt and logic changes in staging, and champion new self-service use cases for the digital product roadmap. This is not a strategy role — it is a hands-on, daily-execution position for a conversational AI specialist who is equally comfortable in conversation data, NLU models, LLM prompt engineering, and business performance analytics.
Why This Is One of the Most Unique Conversational AI Roles Available in the UAE in 2026: Conversational AI Service Managers who can operate at the intersection of GenAI/LLM monitoring, NLU model optimization, bot resolution performance management, and airline customer experience — in real time, every day, at the scale of a major international carrier — represent one of the rarest and most commercially impactful specialist profiles in the UAE’s AI and digital customer operations market. Etihad’s Journey 2030 ambition and its commitment to AI-powered passenger self-service make this a role where your work genuinely shapes how millions of passengers experience one of the world’s most recognized airlines.
Key Accountabilities
Daily Conversation Deep-Dives & Performance Monitoring
- Conduct daily deep-dive analyses of chat transcripts and IVR voice call records — systematically tracing passenger user journeys, identifying friction points, and diagnosing exactly why specific passenger queries failed to resolve or dropped off to live agents
- Review daily “Bot Resolution” and “Containment” metrics rigorously — isolating the high-volume query categories that are repeatedly and unnecessarily transferring passengers to live agents and developing targeted optimization plans to resolve them autonomously
- Monitor and analyze fallout logs, unhandled intent volumes, and “I did not understand” fallback rates — identifying systematic NLU recognition failures that require immediate training phrase additions and intent re-classification
- Regularly review fallback logs during high-volume periods to identify patterns of misunderstood passenger intents — particularly complex routing queries, multi-leg rebooking, and specific baggage or disruption inquiries that require NLU refinement
AI Hallucination Elimination & LLM/GenAI Governance
- Actively monitor GenAI and LLM-driven conversational responses in real time — catching hallucinations, factual inaccuracies, off-brand phrasing, and policy misrepresentations before they reach high passenger volumes and cause reputational or operational harm
- Adjust guardrails, refine prompt templates, and update knowledge base inputs immediately when anomalies are identified — implementing prompt-level and logic-level corrections that eliminate inaccurate AI behavior at the source
- Ensure that the underlying knowledge sources the AI pulls from — including baggage policies, flight change rules, disruption handling procedures, and fare conditions — are accurate, consistently structured, and properly ingested so the bot never surfaces outdated or incorrect policy data to passengers
- Develop and maintain a hallucination monitoring and response protocol — systematically documenting identified AI inaccuracies, root causes, corrections applied, and validation outcomes to build an organizational knowledge base of GenAI failure patterns and mitigations
NLU Model Tuning & Conversational AI Optimization
- Re-classify unhandled passenger inputs on a daily basis — adding training phrases, refining entity definitions, adjusting intent hierarchies, and fine-tuning the Natural Language Understanding (NLU) model continuously to ensure high intent recognition accuracy across all passenger query types
- Optimize bot logic flows and intent mapping architectures for the high-volume queries that are most frequently failing to resolve autonomously — redesigning conversation paths that reduce agent escalation and improve passenger self-service completion rates
- Safely test all prompt adjustments, logic flow changes, copy revisions, and NLU training updates in staging environments — validating improvement impact against daily conversation performance baselines before promoting changes to the live production environment
- Monitor bot performance trends over time — tracking bot resolution rate trajectory, containment improvement, and NLU accuracy gains week-on-week and month-on-month to demonstrate the business value of daily optimization work
New Self-Service Use Cases & Digital Product Roadmap
- Identify emerging passenger pain points, new query category trends, and untapped channel opportunities through systematic daily conversation analysis — translating these insights into prioritized business cases for new AI self-service capabilities
- Champion new self-service use cases for the digital product roadmap — including automated flight rebooking, instant disruption status tracking, seat upgrade flows, and baggage claim assistance — that will further increase passenger self-service rates and reduce contact center volume
- Collaborate with digital product managers, AI platform teams, and customer experience stakeholders to translate identified opportunities into scoped, deliverable product requirements that can be implemented and measured within the conversational AI platform
Qualifications & Requirements
Educational Requirements
- Bachelor’s Degree or equivalent in Computer Science, Information Systems, Digital Technology, or a closely related technical discipline — mandatory educational qualification for this position
Experience Requirements
- 7+ years of professional experience in digital customer operations, contact center technology, or digital product management — with strong exposure to AI-powered customer service platforms and digital self-service programs
- At least 3 years of dedicated, hands-on experience managing conversational AI platforms, chatbot systems, or voice bot applications — operating these systems in a production environment at meaningful passenger or customer scale
- Proven ability to conduct daily analytical reviews of conversation data, identify failure patterns, and implement NLU model improvements in real time — this is the core daily practice of this role
Technical Skills
- Hands-on experience with LLM-powered or GenAI-driven conversational AI platforms — with demonstrable ability to monitor responses, identify hallucinations, adjust prompt guardrails, and validate corrections in staging
- NLU model management experience — training phrase development, intent classification, entity definition, and fallback analysis within a commercial conversational AI or chatbot platform
- Strong understanding of bot resolution metrics, containment rates, and conversation analytics — able to interpret these metrics and translate them into prioritized, specific technical optimization actions
- Knowledge base management and AI content governance experience — ensuring accuracy, structure, and timely ingestion of policy content that powers AI-generated responses to passenger queries
About Etihad Airways & Journey 2030
Etihad Airways is more than the UAE’s national airline — it is an organization actively shaping the future of global aviation. Headquartered in Abu Dhabi, Etihad connects passengers across continents and cultures while executing its Journey 2030 ambition — doubling its fleet, expanding its global network, and growing its people for a bold new era of aviation excellence. As part of this transformation, Etihad is investing heavily in AI-powered passenger experience innovation — deploying conversational AI across every digital touchpoint to give passengers faster, more accurate, and more empowering self-service options that reduce friction and strengthen loyalty. The Conversational AI Service Manager sits at the operational heart of this transformation — ensuring that every AI-powered passenger interaction is accurate, helpful, on-brand, and consistently improving toward the autonomous service excellence that Journey 2030 demands.
Your Career Growth Path: Conversational AI Service Manager → Head of Digital Self-Service → VP Digital Customer Experience → Chief Digital Officer — a uniquely specialist, globally prestigious, and professionally consequential AI career trajectory built at the intersection of enterprise AI operations and world-class aviation customer experience.
Who Should Apply?
- Conversational AI Managers: With 3+ years of production chatbot or voice bot management experience and hands-on NLU model optimization and bot resolution performance management skills
- LLM / GenAI Operations Specialists: With experience monitoring generative AI responses, eliminating hallucinations, and governing prompt templates and guardrails in live customer-facing production environments
- Contact Center Digital Transformation Leads: With 7+ years of digital customer operations experience who have managed AI-powered self-service across multi-channel customer communication platforms
- Chatbot NLU Specialists: With daily NLU training, intent classification, training phrase development, and conversation analytics experience on commercial-scale bot platforms serving large customer volumes
- Airline / Aviation Digital Professionals: With conversational AI, IVR, or digital self-service experience in the airline, travel, or hospitality sector — particularly valuable for understanding passenger query complexity
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