Lead AI Engineer – Computer Vision & Agentic AI

Eazli | Future Living, headquarter in Jeddah, Saudi Arabia is redefining how the Middle East lives, designs, and builds, an AI-native marketplace connecting homeowners with products and home services across Saudi Arabia, the UAE, and Egypt. Built on a multi-language models and a fleet of specialized AI agents, we’re not a startup chasing trends; we’re architecting the infrastructure layer of the MENA home economy, with ambitions stretching into Europe and beyond. If you want to work on real AI that converses, reasons, and transacts at scale, and you want your work to matter to millions of people making their most personal spaces their own - Eazli is where that happens.

We are developing an ecosystem powered by Large Language Models, Computer Vision, Knowledge Graphs, and specialized AI Agents that help homeowners discover products, services, design inspiration, and trusted professionals through intelligent interactions.

Our vision is to build autonomous AI systems that reason, observe, transact, and continuously improve at scale.

We are looking for a Senior AI Engineer who can lead AI engineering initiatives across Eazli while remaining deeply hands-on in architecture, development, experimentation, and production operations.

This role is ideal for someone who enjoys building AI systems from research through production deployment and scaling.

Role Overview

As Senior AI Engineer, you will own the design, development, deployment, optimization, and observability of Eazli's AI ecosystem.

You will be responsible for:
- Production-grade AI Agents
- Agentic orchestration platforms
- Computer Vision and Object Detection systems
- RAG and Knowledge Intelligence platforms
- AI infrastructure scalability
- AI experimentation and innovation
- AI observability and performance optimization

You will work closely with Product, Engineering, Data and Leadership teams to define and execute Eazli's AI roadmap.

Key Responsibilities

AI Platform Leadership
- Lead the design and evolution of Eazli's AI architecture and agent ecosystem.
- Own technical decisions across AI infrastructure, models, orchestration frameworks, and deployment strategies.
- Act as an Individual Contributor when required, developing critical AI systems hands-on.

Agentic AI Systems
- Design and implement advanced agentic architectures using LangGraph, LangChain, CrewAI, OpenAI Agents SDK, Multi-Agent frameworks
- Build: Planning agents, Research agents, Marketplace agents, Recommendation agents, Autonomous workflow agents
- Architect agent collaboration, memory, reasoning, tool usage, and orchestration workflows.

Computer Vision & Object Detection
- Design and deploy computer vision solutions for home products, interiors, and service workflows.
- Build systems involving, object detection, image classification, visual search, image embeddings, similarity matching, scene understanding, OCR and document intelligence.
- Work with modern frameworks including, YOLO, Detectron2, OpenCV, TensorFlow, PyTorch.

Production AI Systems
- Design scalable AI services supporting millions of AI interactions.
- Optimize Token consumption, Latency, Throughput, Inference costs, Agent execution efficiency.
- Implement robust AI governance, evaluation, fallback, and resilience mechanisms.

RAG & Knowledge Systems
- Design advanced Retrieval-Augmented Generation architectures.
- Build semantic search systems using Vector databases, Knowledge Graphs, Hybrid Search, Embeddings, Context Engineering.
- Improve factual accuracy and response quality across AI products.

AI Observability & Reliability
- Build observability frameworks for Agent execution, Tool usage, Prompt performance, Model quality, Cost monitoring, Latency tracking.
- Implement monitoring using Arize, LangSmith, OpenTelemetry, Prometheus, Grafana, Custom evaluation frameworks.
- Define and monitor AI KPIs and SLOs.

Research & Innovation
- Continuously evaluate emerging AI technologies.
- Conduct experiments across LLMs, Vision models, Agent frameworks, Multimodal systems, Autonomous workflows.
- Translate research into production-ready solutions.

Required Experience

- 10+ years Data Science engineering experience.
- 4+ years hands-on AI engineering experience.
- 4+ years hands-on Computer vision engineering experience.
- Strong experience building production AI systems.
- Strong experience with LLM-based applications and agentic systems.
- Proven experience deploying AI solutions at scale.
- Strong Python development skills.
- Experience with FastAPI and microservices architecture.
- Experience with AWS, Azure, or GCP AI deployments.

What Will Make You Stand Out

- Experience running AI agents in production.
- Experience in developing and executing Computer vision operations.
- Experience optimizing LLM costs at scale.
- Experience with multimodal AI systems.
- Experience building autonomous AI workflows.
- Strong research background.
- Contributions to AI open-source projects.
- Publications, blogs, or conference talks related to AI.

What We Look For

- Builder mindset with strong ownership.
- Deep curiosity and passion for AI innovation.
- Ability to balance research and execution.
- Strong architectural thinking with hands-on delivery.
- Comfortable working in ambiguity and rapidly evolving environments.
- Passion for solving real-world customer problems using AI.