AI Systems Architect & LLM Vector Infrastructure

Swiss Hospitality Company; Riyadh; On-site; SAR 180,000 - 220,000; Full time

Job summary

A leading technology enterprise is seeking a Senior AI Systems Architect to design and implement AI-native application cores. You will be responsible for architecting scalable AI pipelines and retrieval-augmented generation systems, focusing on multi-agent AI systems. The ideal candidate has significant software engineering experience and expertise in vector embeddings, along with strong Python skills. This position requires designing infrastructure using Docker and Kubernetes, optimizing AI systems for performance, and ensuring security in production deployments. Join us in advancing our AI capabilities.

Qualifications

• 5+ years software engineering experience.
• 2+ years building production AI systems.
• Deep knowledge of vector embeddings & similarity search.

Responsibilities

• Design AI-first system architecture for web and mobile applications.
• Architect RAG pipelines using vector databases.
• Implement multi-agent AI systems.

Skills

Software engineering experience

Building production AI systems

Vector embeddings & similarity search

Tokenization and context window optimization

Prompt evaluation frameworks

Experience with Python

Experience with FastAPI

Experience designing scalable APIs

Tools

Docker

Kubernetes

PostgreSQL

Job description

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

• 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
• 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
• 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
• AI Agent Systems & Orchestration
• Build autonomous AI agents
• Design tool-calling systems
• Integrate with:
  • n8n
  • LangGraph / LangChain style agent flows
• Implement memory-aware agents
• 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)

Requirements

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