AI Engineer

About The Company:

An AI-powered platform built for real estate investors and asset managers. It transforms fragmented financial, technical, and commercial data into clear dashboards and predictive insights—helping real estate professionals optimize performance, reduce costs, and make smarter, faster decisions. Designed for strategic decision-making in real estate, the platform uses advanced AI to make complex analysis and insights generation fast, intuitive, and fully automated. By combining innovation with intelligence, We are redefining how the industry leverages data and AI—setting a new standard for modern real estate management.

About The Role:

We’re looking for a talented and hands-on AI Engineer to lead the development of intelligent systems powering our platform. The ideal candidate is highly proficient in Python, has deep experience working with GPT agents, and is skilled in building custom AI models from scratch. A strong background in data handling and Retrieval-Augmented Generation (RAG) architectures is a must.

You’ll take ownership of designing and implementing AI-driven features, working closely with our product and engineering teams to integrate them into real-world solutions.

Responsibilities:

Design and build LLM-powered features using GPT agents and RAG pipelines

Implement custom machine learning models tailored to product needs

Work extensively with structured and unstructured data pipelines, preprocessing, and transformation

Research, evaluate, and implement state-of-the-art AI tools and frameworks

Collaborate with developers to integrate AI systems into the platform

Monitor model performance and iterate for continuous improvement

Requirements:

Strong Python skills with 3+ years of experience in AI/ML projects

Hands-on experience with GPT agents (e.g., LangChain, OpenAI tools, etc.)

Deep understanding of Retrieval-Augmented Generation (RAG) and vector databases

Proven ability to work with large datasets, including data cleaning, transformation, and optimization

Experience in training and fine-tuning models from scratch using frameworks like PyTorch or TensorFlow

Familiarity with LLM hosting, inference, and performance tuning

Self-driven, curious, and capable of independently solving complex problems

Nice To Have:

Understanding of data privacy and security in AI applications

Cloud deployment experience (e.g., Firebase, AWS, GCP) pipelines