AI Architect
- Abu Dhabi, United Arab Emirates
Posted 7 days ago
About the role
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 .
Interested candidates please do share your updated CV to mubeenakamal.basha@htcinc.com mentioning your Current CTC, expected CTC and notice period details.
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