معماري أنظمة AI - LLM وبنية المتجهات

We are seeking a senior AI Systems Architect to design and implement AI-native application cores where Large Language Models (LLMs), vector databases, retrieval systems, and agent frameworks form the primary computational layer of our web and mobile applications.
This role is responsible for architecting scalable AI pipelines, retrieval-augmented generation (RAG) systems, memory architectures, AI agents, and orchestration workflows integrated with our development stack (Web, Mobile, n8n automation, and AI services).
The ideal candidate understands that AI is not a feature, it is the operating system of the product.
Key Responsibilities

1. AI Core Architecture Design
   Design AI-first system architecture for web and mobile applications
   Architect RAG pipelines using vector databases
   Define long-term memory, short-term memory, and contextual state systems
   Implement multi-agent AI systems
   Design AI orchestration layers
2. Vector Database & Embedding Systems
   Select and implement vector databases such as:
   Pinecone
   Weaviate
   Qdrant
   Milvus
   Supabase (pgvector)
   Optimize embedding strategies
   Implement hybrid search (semantic + keyword)
   Design scalable indexing pipelines
3. LLM Integration & Optimization
   Work with models such as:
   OpenAI APIs
   Anthropic
   Meta (LLaMA)
   DeepSeek
   Alibaba (Qwen)
   Implement structured output pipelines
   Design evaluation and prompt testing frameworks
   Optimize cost-performance ratio
4. AI Agent Systems & Orchestration
   Build autonomous AI agents
   Design tool-calling systems
   Integrate with:
   n8n
   LangGraph / LangChain style agent flows
   Implement memory-aware agents
5. Production AI Engineering
   Build monitoring systems for hallucination detection
   Design guardrails and validation layers
   Implement evaluation datasets and benchmarking
   Ensure security of AI pipelines
   Build scalable infrastructure (Docker, Kubernetes, GPU optimization)
   Technical Expertise
   5+ years software engineering experience
   2+ years building production AI systems
   Deep knowledge of:
   Vector embeddings & similarity search
   RAG architectures
   Tokenization and context window optimization
   Fine-tuning & LoRA concepts
   Prompt evaluation frameworks
   Experience with Python (mandatory)
   Experience with FastAPI / backend services
   Experience designing scalable APIs
   Architecture Experience
   Designing distributed systems
   Microservices & event-driven architecture
   Experience with PostgreSQL + pgvector
   Experience deploying LLM systems in production

Apply directly at ستار