AI Engineer

About DoorLoop

ֿDoorLoop is property management software built for speed and the smart choice for people who take growth seriously. With offices in Miami, New York City, and Tel Aviv, we’re a global company helping property owners and managers move faster, scale smarter, and get real support, real fast.

We’re proudly People First. That’s why we’re a Certified Great Place to Work, recognized by Forbes as one of America’s Best Startup Employers in both 2024 and 2025, and earn top ratings on Glassdoor.

About the Role

Doorloop is seeking a highly skilled AI Engineer to design and implement complex, multi-agent systems powered by LLMs.

In this role, you will build and orchestrate AI agents using LangGraph and LangChain, manage stateful conversations, and support scalable RAG pipelines that connect external knowledge sources to reasoning agents. You’ll work closely with product and backend teams to deliver real, production-grade AI capabilities.

Responsibilities

• Agent Orchestration: Design, build, and maintain networks of LLM-powered agents that collaborate, share context, and reason together to execute complex workflows.
• LangGraph Architecture: Implement and manage LangGraph graphs that handle message memory, context persistence, and multi-step task coordination.
• RAG Pipelines: Optimize RAG systems to enrich agent reasoning with relevant, up-to-date information.
• Prompt & API Composition: Build modular prompt templates and API calls that agents use for reasoning, retrieval, and action execution.
• Integration & Deployment: Work with engineers to integrate the agentic framework into production systems via APIs and backend services.
• Evaluation & Iteration: Implement evaluation frameworks to measure performance, reliability, and consistency of AI responses across multi-agent pipelines.
• Cross-Team Collaboration: Partner with product and engineering teams to align AI behaviors with real user workflows and KPIs.

• 2+ years as an AI Engineer.
• Hands-on experience building with LangChain and/or LangGraph, including agent orchestration and state management.
• Strong Python skills (TypeScript's a plus), with experience integrating LLM pipelines and external APIs.
• Proven ability to design and deploy autonomous agents with tool use, memory, and reasoning capabilities.
• Familiarity with vector databases (e.g., Pinecone, FAISS, Weaviate) and RAG architectures.
• Deep understanding of prompt engineering, context windows, and structured reasoning chains.
• Experience deploying and monitoring AI systems in production environments.
• Strong problem-solving, debugging, and architectural design skills.
• Experience with multi-agent orchestration using LangGraph or similar frameworks.
• Familiarity with evaluation frameworks for LLMs (e.g., feedback loops, scoring, trace analysis).
• Experience building LLM-driven APIs and integrating them into production software.
• B.Sc in Computer Science, Machine Learning, or a related field.