HTC Global Services — a leading CMM Level 5 global IT and Business Process Services provider headquartered in Troy, Michigan, USA, operating since 1990 — is urgently hiring an AI Engineer with Airline Domain experience for a 1-year extendable onsite contract in Abu Dhabi, UAE. This is a technically sophisticated, production-grade AI engineering role building and maintaining LLM-driven enterprise applications for an airline industry client — covering MCP/FastMCP tools, LangChain, LangGraph, multi-agent architectures, WebSocket streaming, Redis, Azure AI Foundry, and Angular-based conversational UIs. Immediate joiners strongly preferred.
How to Apply — Immediate Action Required
Email your CV to: mubeenakamal.basha@htcinc.com
Subject Line: AI Engineer — Airline Domain — Abu Dhabi UAE 2026
Include in your email: Current CTC · Expected CTC · Notice Period / Availability
Preferred: Immediate joiners and candidates with short notice periods
Contract: 1-year extendable onsite contract — Abu Dhabi, UAE
About HTC Global Services — Global CMM Level 5 IT Services Leader
Company: HTC Global Services — Leading CMM Level 5 Global IT & Business Process Services Provider
Founded: 1990 | Headquarters: Troy, Michigan, USA | Global Operations across multiple continents
Specialization: Innovative IT solutions · Business Process Services · Enterprise technology delivery
Credential: CMM Level 5 — the highest maturity level in software engineering process excellence
Client: Major Airline Industry enterprise client in Abu Dhabi — large-scale AI platform in production
Why This HTC Global AI Engineer Role in Abu Dhabi Is a High-Value Contract Opportunity
Airline AI at Enterprise Scale: Building LLM-driven applications for a major airline client in production — real enterprise AI, not prototype work; direct impact on airline operations and passenger-facing services
Full Modern AI Stack: MCP, LangChain, LangGraph, multi-agent architectures, Azure AI Foundry — one of the most comprehensive and current AI engineering stacks available in the UAE contract market
CMM Level 5 Organization: HTC Global Services’ process maturity ensures a structured, professional, and well-governed delivery environment — a high-quality contract experience with a globally recognized IT services brand
Tax-Free Abu Dhabi: Competitive contract compensation — zero personal income tax in Abu Dhabi, UAE
Position Overview
This AI Engineer — Airline Domain contract role at HTC Global Services in Abu Dhabi is a technically demanding, full-stack AI engineering position working on enterprise-grade LLM applications for an airline industry client in a live production environment. You will build and maintain LLM-driven enterprise applications, design and develop MCP (Model Context Protocol) tools using Python and FastAPI, maintain multiple MCP services and LLM integrations, develop Angular-based conversational user interfaces with real-time WebSocket updates, design scalable architectures for high-concurrency AI workflows, implement monitoring, logging, and tracing, optimize latency, cost, and response quality continuously, implement and support multi-agent architectures with context sharing and orchestration, use Redis for caching, session management, and conversation memory, and maintain services for conversation state, workflow, and memory handling. This role requires genuine production AI engineering experience — not just familiarity with LLM libraries, but the systems thinking, performance optimization discipline, and production deployment experience that enterprise-scale airline AI applications demand.
Why This HTC Global AI Engineer Contract in Abu Dhabi Is the AI Engineering Opportunity of 2026: AI engineers who combine genuine production LLM application development experience with MCP/FastMCP tool building, LangChain and LangGraph multi-agent orchestration, Python FastAPI async backend development, Angular-based conversational UI, Redis-based session and memory management, and Azure AI Foundry deployment — working specifically in the airline domain where AI applications directly impact operational efficiency and passenger experience at scale — are among the most technically credentialed and commercially sought-after AI engineers in the UAE contract market in 2026. The combination of HTC Global’s CMM Level 5 credibility, the airline domain specificity, and the comprehensive modern AI stack makes this Abu Dhabi contract one of the most technically valuable and CV-enhancing AI engineering engagements available in the region.
Key Responsibilities
LLM-Driven Enterprise Application Development — Airline Domain
- Build and maintain LLM-driven enterprise-level applications in a real production environment — delivering the reliability, performance, observability, and operational excellence that airline industry enterprise applications require, including robust error handling, graceful degradation, and the continuous monitoring and alerting that keep production AI systems operating safely and efficiently for airline operational teams and passengers
- Design and develop MCP (Model Context Protocol) tools using Python, FastAPI, or similar frameworks — building the structured, protocol-compliant tool layer that enables LLMs to reliably invoke airline domain-specific capabilities, access airline data systems, and perform actions within airline workflows through well-defined tool interfaces that maintain security, auditability, and performance standards
- Maintain multiple MCP services and LLM integrations — managing the lifecycle of several concurrent MCP service instances and their LLM connections, ensuring service health, version compatibility, and integration reliability across the full set of LLM-powered capabilities deployed for the airline domain client
- Continuously optimize latency, cost, and response quality in production LLM applications — applying a systematic approach to LLM application performance engineering that balances user experience (response speed and quality), operational economics (token costs and compute utilization), and system reliability across the varying load patterns of an airline’s operational calendar
Multi-Agent Architecture — Design, Orchestration & Context Management
- Implement and support multi-agent architectures with context sharing and orchestration — designing and building the agent coordination frameworks, role-based agent structures, task decomposition strategies, and fallback mechanisms that enable complex airline domain workflows to be executed reliably by orchestrated teams of specialized AI agents rather than monolithic single-agent systems
- Apply strong understanding of agent orchestration patterns including role-based agents, task decomposition, coordination, and fallback mechanisms — using LangGraph, LangChain agent frameworks, or custom orchestration logic to build multi-agent systems that handle the complex, multi-step reasoning and action sequences that airline domain workflows require
- Implement prompt engineering, structured outputs, tool calling patterns with awareness of model limitations and failure modes — applying sophisticated prompt design, output format specification, and tool invocation patterns that produce reliable, parseable AI outputs even when operating near the edges of LLM capability in the complex, factually demanding airline domain
- Maintain scalable services for conversation state, workflow management, and memory handling — building the stateful application layer that maintains coherent, contextually aware AI interactions across multi-turn airline domain conversations, correctly managing conversation history, workflow progress, user preferences, and session-specific context throughout extended interactions
Frontend — Angular Conversational UI & Real-Time WebSocket Streaming
- Develop Angular-based conversational user interfaces with real-time updates — building the responsive, professional, and airline-brand-appropriate chat interfaces and AI-powered frontend experiences that give airline operational users and passengers fluid, natural access to LLM-powered capabilities through well-designed conversational UI patterns
- Implement WebSocket-based communication for streaming AI responses — engineering the real-time connection management, streaming message rendering, partial update handling, and connection resilience that make streamed LLM responses feel responsive and polished in the Angular-based user interface, even during high-load periods
- Apply RxJS and reactive programming patterns for real-time UI updates — using Angular’s reactive programming model effectively to manage the complex, asynchronous data flows that streaming AI responses, real-time status updates, and multi-agent workflow progress notifications require in a production airline AI application
Backend, Infrastructure & Cloud — Python, Redis, Azure AI Foundry
- Design scalable architectures capable of supporting high concurrency for airline domain AI workflows — applying distributed systems design principles, async Python patterns, and Azure infrastructure capabilities to build AI application backends that handle the concurrent user load of an airline’s operational environment without performance degradation
- Use Redis for caching, session management, and conversation memory — implementing Redis-based caching strategies that reduce LLM API costs by avoiding redundant calls, manage user session state reliably across stateless service instances, and maintain conversation memory efficiently across the multi-turn dialogue sessions characteristic of airline domain AI interactions
- Implement monitoring, logging, and tracing for AI workflows — deploying the observability infrastructure (Azure Monitor, OpenTelemetry, or equivalent) that gives operations teams real-time visibility into AI application health, LLM call performance, agent execution traces, error rates, and the other metrics essential for managing production AI systems with confidence
- Work with Azure AI Foundry and Azure GitHub — deploying AI models and services on Azure’s AI platform infrastructure, managing code and infrastructure changes through Azure-integrated GitHub workflows with proper PR processes, branch management, and CI/CD pipeline integration that maintain code quality and deployment reliability across the contract engagement
Profile & Requirements
Technical Requirements
- Demonstrated production experience with LLM-driven application development — not just experimental or tutorial-level familiarity, but genuine live production deployment of LLM-powered features in enterprise applications, with accountability for their reliability and performance
- Proficiency in Python and FastAPI for async backend service development — the core backend language and framework combination for MCP tool building and LLM integration service development in this role
- Experience with LangChain, LangGraph, or equivalent multi-agent AI frameworks — direct hands-on experience designing and implementing agent orchestration patterns in production or near-production AI systems
- Angular or React frontend experience with WebSocket-based real-time communication — for the conversational UI development dimension of this full-stack AI engineering role
- Azure experience — particularly with Azure AI services, Azure GitHub CI/CD workflows, and Azure-hosted infrastructure for AI application deployment
About HTC Global Services & AI Engineering in the Airline Domain — Abu Dhabi 2026
HTC Global Services‘ CMM Level 5 maturity designation reflects the company’s three-decade commitment to software engineering process excellence — the discipline, governance, and delivery consistency that global enterprise clients in demanding industries like aviation trust when deploying business-critical technology. For an AI Engineer joining HTC Global’s Abu Dhabi airline domain engagement in 2026, this process maturity means working within a well-defined, professionally structured delivery environment where engineering standards are taken seriously, technical decisions are well-governed, and the quality of the AI systems being built reflects the operational importance of the airline client they serve. The technical scope of this role — spanning MCP tool engineering, LangChain multi-agent orchestration, LangGraph workflow design, Angular conversational UI, Redis-based memory management, and Azure AI Foundry deployment — represents one of the most technically comprehensive and professionally credentialing AI engineering engagements available in the UAE contract market. For the right AI engineer, this Abu Dhabi contract is the engagement that builds the production airline AI engineering experience that will define the next chapter of their career.
Your Career Growth Path: AI Engineer — Airline Domain → Senior AI Engineer → AI Solutions Architect → Principal AI Engineer → Head of AI Engineering — a globally valued, technically specialized, and airline-domain-credentialed AI engineering career built on one of the most modern and comprehensive AI stacks deployed in the UAE’s enterprise aviation sector in 2026.
Who Should Apply?
- Full-Stack AI Engineers (Python + Angular + LLM): With production LLM application development, FastAPI backend, and Angular conversational UI experience who want an onsite Abu Dhabi contract working on enterprise airline AI at HTC Global Services
- LangChain / LangGraph Engineers: With multi-agent architecture design and implementation experience, MCP tool building skills, and Redis-based session management knowledge who want to apply their AI engineering specialism in the airline domain
- Airline Domain AI Specialists: With prior AI or software engineering experience in the airline or aviation sector who want to combine their industry knowledge with LLM engineering in a contract role for a major airline client in Abu Dhabi
- Azure AI Foundry Engineers: With Azure AI platform deployment, Azure GitHub CI/CD, and cloud-native AI infrastructure experience who want a technically comprehensive AI engineering contract in the UAE
- Immediate Joiners — AI Engineers: Currently available or on short notice who want a well-structured, CMM Level 5 IT services company contract in Abu Dhabi’s active enterprise AI market for 2026
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