AI Systems Architect📣 إعلان

منذ ساعتين تقريبا

	نوع العقد	دوام كامل
	طبيعة الوظيفة	بالموقع
	الموقع	الرياض

وصف الوظيفة

About the AI Systems Architect Role

We are seeking a senior AI Systems Architect for a full-time position in Riyadh, Riyadh Province. This role involves designing and implementing AI-native application cores where Large Language Models (LLMs), vector databases, retrieval systems, and agent frameworks form the primary computational layer for web and mobile applications. The ideal candidate understands that AI functions as the operating system of the product, not merely a feature.

Key Responsibilities

The AI Systems Architect will be responsible for architecting scalable AI pipelines, Retrieval-Augmented Generation (RAG) systems, memory architectures, AI agents, and orchestration workflows integrated with our development stack. Key responsibilities include:

Design AI-first system architectures for web and mobile applications.
Architect RAG pipelines using vector databases and define long-term, short-term, and contextual state memory systems.
Implement multi-agent AI systems and design AI orchestration layers.
Select and implement vector databases such as Pinecone, Weaviate, Qdrant, Milvus, and Supabase (pgvector).
Optimize embedding strategies and design scalable indexing pipelines, including hybrid search (semantic + keyword).
Integrate and optimize Large Language Models (LLMs) from providers like OpenAI, Anthropic, Meta (LLaMA), DeepSeek, and Alibaba (Qwen).
Implement structured output pipelines and design evaluation and prompt testing frameworks to optimize cost-performance ratios.
Build autonomous AI agents, design tool-calling systems, and integrate with n8n, LangGraph, or LangChain style agent flows, ensuring memory-aware agent functionality.
Develop production AI engineering solutions, including monitoring systems for hallucination detection, guardrails, validation layers, and evaluation datasets for benchmarking.
Ensure the security of AI pipelines and build scalable infrastructure using technologies like Docker, Kubernetes, and GPU optimization.

Technical Expertise

Candidates should possess the following technical qualifications:

5+ years of software engineering experience.
2+ years of experience building production AI systems.
Deep knowledge of vector embeddings & similarity search, RAG architectures, tokenization and context window optimization, fine-tuning & LoRA concepts, and prompt evaluation frameworks.
Mandatory experience with Python.
Experience with FastAPI or other backend services.
Experience designing scalable APIs.