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Build Technologies

AI Engineer - Assistant Experience

New York City$120k–$240kfulltimemidAdded today

About this role

Build is seeking an AI Engineer to enhance Dougie, their agentic AI system for real estate workflows. You'll implement memory systems, integrate grading into execution loops, and reduce human-in-the-loop time while ensuring reliable production performance across complex automation tasks.

What you'll do

  • Own and expand Dougie's capabilities across Build's digital labor ontology end-to-end
  • Integrate grading and evaluation directly into the execution path to enable self-improving runs
  • Build memory layers that preserve institutional context across agent sessions
  • Instrument and systematically reduce human-in-the-loop time weekly
  • Improve agent orchestration including planning, tool use, and failure recovery
  • Debug non-deterministic systems rigorously and own agent behavior in production

What they're looking for

  • Agentic AI systems and unattended autonomous execution
  • Memory architecture, context management, and retrieval systems
  • Agent orchestration and tool integration
  • Production debugging and observability for non-deterministic systems
  • Human-in-the-loop workflow design and optimization
  • Real estate domain knowledge or vertical AI experience
  • Python and system design
  • Feedback loops and learning from production data

Benefits

  • Radical autonomy with minimal bureaucracy and end-to-end ownership
  • Meaningful, generous equity
  • High-impact work on institutional real estate automation
  • Collaboration with ex-Blackstone and OpenAI leadership
  • Fast-shipping, intensity-driven culture
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Build Technologies

Build Technologies develops core infrastructure and agentic AI systems designed for real estate and built-world enterprises operating in production environments. The company is hiring AI engineers to build agent runtimes, evaluation systems, retrieval layers, and observability platforms that power reliable, scalable AI workflows.

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Likely interview questions

  • Walk us through a time you built an agentic system that ran unattended in production—what went wrong and how did you fix it?
  • How would you design a memory layer that allows an agent to improve its behavior across multiple sessions without manual retraining?
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