AI Architect

HTC Global Services; Abu Dhabi Emirate; On-site; AED 300,000 - 520,000; Full time

Job summary

HTC Global Services is seeking an AI Architect for a 1-year extendable on-site contract in Abu Dhabi. The role focuses on designing and deploying Agentic AI platforms, integrating LLMs with enterprise systems, and building scalable, secure AI architectures.

The candidate should have deep expertise in MCP, vector databases, guardrails, evaluation frameworks and cost-aware design, with strong Python and cloud AI experience.

Qualifications

• Strong hands-on experience designing, building and deploying production-grade Agentic AI applications.
• Deep understanding of LLM capabilities and implementation patterns.
• Experience with LLM orchestration frameworks and patterns.
• Hands-on experience designing RAG pipelines including embeddings and vector search.
• Experience with vector databases and search technologies.
• Strong understanding of MCP architecture and integrations.
• Experience integrating AI agents with APIs and tools.
• Experience implementing AI guardrails and responsible AI practices.
• Experience defining evaluation frameworks and monitoring for AI apps.
• Ability to optimize latency, quality, reliability, scalability and cost.
• Proficiency in Python and backend frameworks.

Responsibilities

• Define end-to-end AI solution architecture and governance.
• Lead design reviews and set engineering standards for AI systems.
• Oversee integration of AI agents with enterprise apps and data sources.

Skills

Agentic AI

Generative AI

LLMs

LLM Orchestration

RAG

Vector Databases

MCP

AI Tool Integration

AI Guardrails

AI Evaluation

AI Performance

Python

Cloud AI Platforms

Data Integration

MLOps/LLMOps

Containers & Deployment

Security & EA

Architecture Leadership

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

CrewAI

Azure AI Search

Pinecone

Weaviate

Milvus

pgvector

FAISS

MCP servers

REST APIs

GraphQL

Job description

Exciting Opportunity Alert! HTC Global Services is hiring AI Architect for an 1-year extendable contract in Abu Dhabi, UAE (Onsite).

HTC Global Services - a leading CMM level 5 global provider of innovative IT and Business Process Services and Solutions since 1990 with headquarters in Troy, Michigan, USA.

Technical Skills & Expertise

• Agentic AI & Generative AI: Strong hands-on experience designing, building and deploying production-grade Agentic AI applications, including autonomous and multi-agent workflows, AI agents, planning and reasoning patterns, memory, tool usage and human-in-the-loop systems.
• Large Language Models (LLMs): Deep understanding of LLM capabilities, limitations and implementation patterns, including prompt engineering, structured outputs, function/tool calling, context management and model selection.
• LLM Orchestration: Experience with LLM orchestration frameworks and patterns such as LangChain, LangGraph, Semantic Kernel, AutoGen, CrewAI or similar technologies.
• Retrieval-Augmented Generation (RAG): Hands-on experience designing and optimizing RAG pipelines, including document ingestion, chunking strategies, embeddings, vector search, retrieval, reranking, context optimization and grounded response generation.
• Vector Databases & Knowledge Retrieval: Experience working with vector databases and search technologies such as Azure AI Search, Pinecone, Weaviate, Milvus, pgvector, FAISS or similar platforms.
• Model Context Protocol (MCP): Strong understanding and practical experience with MCP architecture, including building and integrating MCP servers, tools, resources and AI-agent integrations.
• AI Tool Integration: Experience integrating AI agents with enterprise applications, APIs, databases and external tools using REST APIs, GraphQL, SDKs, function calling and event-driven architectures.
• AI Guardrails & Responsible AI: Experience implementing AI safety and governance mechanisms, including guardrails, content filtering, prompt injection protection, PII protection, access controls, human approval workflows and responsible AI practices.
• AI Evaluation & Observability: Strong experience defining and implementing evaluation frameworks for AI applications, including automated and human evaluation, benchmarking, hallucination detection, quality metrics, tracing, monitoring and feedback loops.
• AI Performance & Cost Optimization: Ability to evaluate and optimize trade-offs between latency, quality, reliability, scalability and cost, including model selection, caching, token optimization and efficient AI architecture design.
• Python & Software Engineering: Strong hands-on programming expertise in Python, with experience building scalable, production-grade applications. Experience with FastAPI or similar backend frameworks is highly desirable.
• Cloud AI Platforms: Hands-on experience with one or more cloud AI ecosystems, preferably Microsoft Azure, including services such as Azure AI Foundry, Azure OpenAI, Azure AI Search, Azure Machine Learning, Databricks or equivalent AWS/GCP AI services.
• Data Engineering & Integration: Good understanding of enterprise data architecture, including structured and unstructured data, APIs, databases, data pipelines, streaming/event-driven systems and knowledge ingestion pipelines.
• MLOps / LLMOps: Experience with CI/CD, model and prompt versioning, deployment automation, experimentation, monitoring, observability and lifecycle management for AI and ML applications.
• Containers & Deployment: Experience with Docker, Kubernetes and modern cloud-native deployment practices.
• Security & Enterprise Architecture: Understanding of enterprise security principles, including authentication, authorization, secrets management, API security, data privacy and secure AI application design.
• Architecture & Technical Leadership: Ability to define end-to-end AI solution architecture, establish engineering standards, conduct code and architecture reviews, and guide teams on reusable patterns and technical best practices.

Technical Experience Required

• 8+ years of experience in software engineering, AI/ML, data engineering or related technical domains.
• Strong hands-on experience building and deploying Generative AI, LLM and Agentic AI solutions into production.
• Proven experience with LLM orchestration, RAG, tool calling, MCP integrations, vector databases, guardrails and AI evaluation frameworks.
• Strong proficiency in Python and modern software engineering practices.
• Experience designing scalable, secure and reliable enterprise AI architectures.
• Hands-on experience leading technical teams while remaining actively involved in coding, solution design, code reviews and architecture decisions.
• Experience defining AI application KPIs, evaluation metrics, feedback loops and production monitoring.
• Ability to make technical decisions based on business value, feasibility, security, scalability, latency, quality and cost.

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