Senior AI Engineer

York Towers is the development arm of the York Holding Group. Through continuous research and the ability to predict emerging trends, the company keeps an edge over the market. Playing a leading role in driving the successful development and diversification of one of the most vital economic sectors, York Towers is committed to creating residential products across the country that provide residents with distinctive, universal, multicultural, and enriching lifestyles. York Towers is the exclusive developer of luxury real estate worldwide. The company aims to become a leading real estate player through an efficient business model and advanced technologies used for designing and construction. Since its establishment in 2016, York Towers has delivered 20 real estate properties and runs six dynamic projects. York Towers operates eight offices in five countries across three continents.

About Dwelleo

Dwelleo is an AI-powered real estate marketplace transforming how people search, buy, sell, and rent properties across Saudi Arabia.

The platform combines machine learning, intelligent discovery tools, and data-driven insights to connect buyers, renters, brokers, and developers through a seamless, scalable digital experience.

At its core, Dwelleo embeds AI directly into the product — powering pricing, recommendations, search, and decision-making across the entire property journey.

About The role

You'll work across the full AI surface area of a live product. Your work will span classical ML (pricing, forecasting) and modern LLM systems (agents, RAG, voice), with real engineering expectations around reliability, observability, and production quality. Research here is always in service of shipping — experimentation exists to accelerate delivery, not replace it.

You'll work within a dual-track Agile structure: a Research sprint for experimentation and model development, and an Engineering sprint for deployment, integration, and reliability work. You'll contribute to both.

What you'll do

• Ship predictive models for property price estimation, rent forecasting, and ROI analysis — from feature engineering through production deployment on AWS ECS with canary release practices
• Build and maintain LLM-powered multi-agent systems, including deterministic state machines, scoring engines, guardrail layers, and escalation logic that runs reliably at scale
• Develop and improve RAG pipelines with vector-based retrieval (FAISS, pgvector) for property search and AI-assisted advisory features
• Expose AI capabilities as FastAPI microservices with autoscaling, versioning, and production-grade reliability
• Integrate and improve STT/TTS speech pipelines connected to telephony infrastructure — Arabic dialect support is a meaningful plus
• Own observability across the stack: drift detection, latency monitoring, alerting, and model performance dashboards
• Collaborate closely with product and engineering across both sprint tracks, translating research outcomes into shippable systems
  
  

What we're looking for

Required:

• 4+ years of hands-on experience in ML engineering, AI engineering, or a closely related role — with at least some of that time shipping to production
• Strong Python skills with a track record of production deployment (not just notebooks)
• Solid ML fundamentals: supervised learning, gradient boosting (XGBoost / LightGBM), feature engineering, model evaluation, and retraining workflows
• Hands-on experience with LLMs (OpenAI, Anthropic, or open-source models) and practical RAG pipeline implementation
• Experience building and deploying ML microservices using FastAPI
• Working knowledge of CI/CD for ML workloads — you've set up or maintained pipelines using tools like GitHub Actions, MLflow, or equivalent
  
  

Nice to have:

• STT/TTS integration or voice pipeline engineering — Arabic dialect experience is a strong plus
• AWS hands-on experience: ECS, S3, RDS
• Familiarity with geospatial data and similarity search (Ball Tree, FAISS, pgvector)
• Background in lead scoring, content moderation, or recommendation systems
• Experience with MLflow, experiment tracking, or model registry workflows
• Real estate or PropTech domain exposure
  
  

What we offer

• Location: Fully remote
• Team: You'll report directly to the AI Team Lead
• Direct ownership of production AI systems with measurable user and business impact
• A technically ambitious environment working at the intersection of AI and one of the region's most active real estate markets