Applied AI Engineer
Location not statedJobPosted 1 day agoStill listed today
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Job overview
Smart Bricks is seeking Applied AI Engineers to build intelligence systems for institutional real estate workflows. The role involves developing agents that process documents, conduct research, interact with financial models, and produce auditable investment outputs. Engineers will build and evaluate production AI systems, connect them to data and tools, and turn customer workflows into reusable product capabilities. Real estate or finance experience is useful but not required.
Skills & qualifications
Skills
Qualifications
Full job description
Smart Bricks is the applied AI lab for real estate. We are building the intelligence infrastructure for the world’s largest asset class. Our platform combines four intelligences: Company Brain, Real Estate Intelligence, Market Intelligence and Specialist Agents, with Financial Engines under the agents. We operate globally across Dubai, London and San Francisco, bringing together exceptional people from AI, engineering, real estate and finance. We care more about exceptional ability, rate of learning and ownership than conventional credentials.
The role We are looking for exceptional Applied AI Engineers to build the intelligence systems at the core of Smart Bricks. You’ll work on multi-agent systems capable of performing complex institutional real estate workflows: reading thousands of pages of documents, conducting market research, interacting with financial models, reasoning across proprietary datasets and producing auditable investment outputs. This is not a role focused on wrapping APIs in chat interfaces. You’ll be responsible for making AI systems reliably perform work that today requires teams of analysts and investment professionals.
What you’ll do
- Build and improve specialised AI agents for institutional real estate workflows
- Design multi-agent orchestration, planning, tool-use and reasoning systems
- Build retrieval and context systems across structured and unstructured information
- Connect agents to financial models, proprietary data and external tools
- Develop evaluation frameworks for accuracy, reliability and performance
- Improve agent latency, cost and reasoning quality
- Work with Forward Deployed teams to turn customer workflows into reusable product capabilities
- Ship continuously into production
What we’re looking for
- Exceptional software engineering fundamentals
- Deep practical experience building production LLM applications
- Experience with agents, RAG, tool use, context engineering or model evaluation
- Strong Python and modern AI infrastructure experience
- Comfort operating in ambiguous, rapidly changing environments
- Obsession with making AI systems actually work reliably
Experience in real estate or finance is useful, but not required.
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