Lead AI Engineer

DoorLoop; Illinois; On-site; USD 90,000 - 150,000; Full time

Job summary

An innovative technology company is seeking a Lead AI Engineer to spearhead the development of AI-driven solutions. This role involves prompt engineering, building AI agents, and integrating AI features into products, all while driving the technical vision from the ground up. The ideal candidate will have extensive experience in AI and prompt engineering, with a strong proficiency in Python and various AI frameworks. Join a dynamic team that values people first and is committed to pushing the boundaries of technology in the property management sector.

Qualifications

• 4+ years of experience as an AI and/or prompt engineer.
• Proven experience building AI agents using frameworks like LangChain.
• Strong analytical and problem-solving skills.

Responsibilities

• Develop, test, and optimize prompts for high-quality AI responses.
• Implement RAG-based solutions to improve AI responses.
• Design, build, and deploy autonomous AI agents.

Skills

Prompt Engineering

AI Agent Development

Python

Analytical Skills

Problem-Solving

Tools

OpenAI API

LangChain

PyTorch

FAISS

Pinecone

Weaviate

Job description

DoorLoop is a high-growth technology (PropTech) company with offices in the US (Miami and NYC) and Israel (Tel Aviv). We help property managers and owners make more money, get organized, and grow with easy-to-use, secure, and reliable, all-in-one property management software.

DoorLoop prides itself on being People First. We are a Certified Great Place to Work, are Forbes America’s Best Startup Employers in 2024 & 2025, and are proud to have our team rate us a 4.9/5 on Glassdoor.

Mission

Doorloop seeks a Lead AI Engineer specializing in prompt engineering and optimizing large language models (LLMs) for real-world applications. In this role, you will not only design effective prompts, improve model responses, and build AI agents, but also take the lead in shaping and delivering the initial AI-powered product for the company. You'll be responsible for driving the technical vision, building from scratch, and leading the implementation of AI-driven capabilities that will become a core part of Doorloop’s product offering.

Responsibilities

• Prompt Engineering: Develop, test, and optimize prompts for high-quality AI responses across different tasks.
• Retrieval-Augmented Generation (RAG): Implement RAG-based solutions to improve AI responses using external knowledge bases.
• Integration & API Development: Work with software engineers to embed AI features into our product via APIs.
• AI Agent Development: Design, build, and deploy autonomous AI agents that can reason, and execute multi-step tasks using LLMs, tools, memory, and APIs.
• Experimentation & Evaluation: Continuously refine models using A/B testing, human feedback loops, and AI evaluation metrics.
• Stay Updated: Keep up with the latest LLM advancements and best practices in the AI industry.
• Product applications: Apply LLMs and agents to real-world scenarios that solve meaningful user problems.
• Product implementation: Work closely with the product team to secure delivery is aligned with expected product requirements
• Response validation: Implement a process to ensure accurate KPI measurement and consistent, expected outcomes.

Requirements

• +4 years of experience as an AI and/or prompt engineer (OpenAI API, Anthropic Claude, etc.).
• Proven experience building AI agents using frameworks like LangChain, AutoGPT, or custom stacks
• Proficiency in Python and AI frameworks (PyTorch, LlamaIndex).
• Deep understanding of tool use, memory, and autonomous task design for agents
• Familiarity with embedding models and vector databases (FAISS, Pinecone, Weaviate).
• Experience working with NLP pipelines, tokenization, and text preprocessing.
• Strong analytical and problem-solving skills.
• Strong business acumen with a proven ability to translate strategic objectives into actionable initiatives.

Preferred Qualifications

• Experience with cloud platforms (AWS, GCP, Azure) for AI deployment.
• Previous experience integrating AI into production systems
• Knowledge of MLOps best practices and CI/CD pipelines for AI models.