AI Team Lead

Dwelleo is a Saudi AI-powered PropTech platform redefining how real estate decisions are made. From buying and renting to selling and investing, we combine verified data, intelligent insights, and complete transparency — empowering users to understand the market clearly and make confident decisions at every step.

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

As AI Lead, you will own both our ML and LLM workstreams : defining the technical architecture, governing production systems, and leading the team that ships them. This is a hands-on leadership position — you are expected to be close to the technical decisions, not just the roadmap.

The immediate scope spans two areas: maturing our ML platform (pricing, forecasting, drift monitoring) and scaling our agentic AI systems into robust, production-grade infrastructure.

You will lead a team of 3–7 engineers, staying hands-on technically while owning delivery, standards, and team growth.

What You'll Do

• Own the full ML lifecycle  — feature engineering, training, evaluation, deployment, and drift monitoring for pricing, rent, and ROI prediction models
• Define the experimentation framework  — data contracts, labelling strategies, A/B testing pipelines, guardrail metrics, and rollback procedures
• Architect production agentic systems  — design LLM-based multi-agent workflows with deterministic state machines, guardrail layers, and escalation logic
• Lead infrastructure and platform decisions  — FastAPI microservices on AWS ECS, model serving, CI/CD (GitHub Actions + MLflow), and end-to-end observability
• Drive research and evaluation  — assess new approaches across supervised learning, NLP, and agentic AI; decide what gets built, what gets dropped, and why
• Lead a team of 3–7 engineers  — set engineering standards, conduct code and design reviews, mentor team members, and participate in hiring as the technical voice
  
  

What We're Looking For

Required

• 6+ years  of ML engineering experience, with at least 3 years in a technical lead or senior individual contributor role
• Production-scale ML: supervised learning, gradient boosting (XGBoost / LightGBM), regression, feature engineering, and model evaluation
• Solid MLOps practice: experiment tracking, model registry, canary deployments, drift detection, and incident response
• 2+ years  working with LLM orchestration, RAG architectures, or multi-agent system design
• Demonstrated experience leading a team of engineers — including hiring, mentoring, setting technical direction, and translating AI capabilities into product outcomes
  
  

Nice to Have

• Experience building and deploying FastAPI-based ML services on AWS (ECS, S3, RDS)
• Experience with speech pipelines (STT / TTS) or multilingual NLP — Arabic dialect knowledge is a strong plus
• Familiarity with geospatial data or similarity search (FAISS, pgvector, Ball Tree)
• Background in lead scoring, recommendation systems, or content moderation
• Real estate, PropTech, or marketplace experience
  
  

What We Offer

• Fully remote
• High ownership over both AI architecture and team direction
• Direct exposure to a complex, multilingual, geospatial AI problem space operating at real market scale