AI Engineer: End-to-End Real Estate Intelligence

United States Digital Space LLC; Paris (TX); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Competitive salary

Meaningful equity

Job summary

Davis is hiring an AI Engineer to work on a multi-agent pipeline that converts raw, fragmented data into expert-grade real estate deliverables. You will make the pipeline reliable, fast, and indistinguishable from the best human teams, then push it beyond what any human team could do, owning the stack end to end—from context engineering to verification, storage and evaluation.

You will work with domain experts, build scalable infra, and drive model evaluation to ensure outputs meet client needs.

Qualifications

• 1.5+ years building and deploying production software at scale.
• Experience building and evaluating LLM agents / multi-step workflows in real systems.
• Proven context engineering experience: reliability depends on assembling the right context.
• Deep Python expertise: typing, async/concurrency, strong testing culture.

Responsibilities

• Harness engineering: design and build the system layer around the model — context assembly, tool orchestration, verification, and report generation.
• Data ingestion & context assembly: handle messy, unstructured project data from heterogeneous sources.
• Storage & traceability: persist sources, extracted facts, intermediate results, report versions, and edits.
• Evaluation & benchmarking: build an internal eval harness to track agents performance over time.

Skills

Python

LLM agents

Context engineering

Databases & data modeling

Full-stack experience

Production software at scale

Tools

APIs

Job description

Davis is hiring an AI Engineer to work on a multi-agent pipeline that converts raw, fragmented data into expert-grade real estate deliverables. You will make the pipeline reliable, fast, and indistinguishable from the best human teams, then push it beyond what any human team could do, owning the stack end to end—from context engineering to verification, storage and evaluation.

You will work with domain experts, build scalable infra, and drive model evaluation to ensure outputs meet client needs.