Senior AI Engineer

November 19

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Homebound

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Real Estate

Homebound is a company that specializes in building and customizing homes for its clients. They offer a seamless process where potential homeowners can choose either a finished home or customize one according to their preferences. Homebound emphasizes thoughtful design, blending traditional elements with modern styles, and allows for customization in a short time. They build homes in desirable and centrally located neighborhoods. The company also partners with Yardzen to offer digital landscape design services and works with top lending partners to provide financing options. With a focus on customer experience, Homebound guides customers through every step of the homebuilding process, from exploration to move-in.

51 - 200 employees

🏠 Real Estate

📋 Description

• Shape the vision for how AI/ML, particularly LLMs, integrate into Homebound’s products and operations. Define technical standards for experimentation, deployment, and evaluation. • Design and build scalable AI systems that can handle real-world production workloads and evolve with the business. • Deliver high-quality, production-grade code daily while ensuring observability, maintainability, and reliability. • Raise the bar across engineering by teaching AI best practices, reviewing designs, and guiding engineers through complex technical challenges. • Stay abreast of the rapidly evolving AI landscape, bringing forward cutting-edge ideas while focusing investment where it creates clear business impact.

🎯 Requirements

• 7+ years of professional software engineering experience, with a strong focus on AI/ML systems. • Shipped LLM-powered features into production, including hands-on experience with prompt engineering, RAG, eval frameworks, and agentic workflows. • Demonstrated leadership, including mentoring teams, influencing technical direction, and being the go-to problem solver for complex AI challenges. • Fluency in Python and experience with core ML/data libraries (e.g., Pandas, Scikit-learn, PyTorch/TensorFlow, Spark). • Proven ability to design systems that balance rapid experimentation with long-term reliability and maintainability.