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 37 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 37 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+ yearsof 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+ yearsworking 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
