Senior AI Engineer

Salary: Not specified Location Type: Not specified Employment Type: Not specified

What we do and why we do it

As the leading end-to-end investment platform for single-family rental homes (SFR), our mission is to make real estate investing radically accessible, cost effective, and simple. We successfully merge our passion for helping investors build wealth through real estate with cutting edge technology that transforms the way they do it.

How it’s going (and growing)

With a talented team of 600+ Roofsters, our collaborative, can-do culture is what fuels our growth. In 2022, we closed on our Series E, raising $240 million, and have offices in California, Texas, and New York as well as many remote opportunities. Our growth includes recent acquisitions of Stessa (financial and asset management software), RentPrep (tenant screening and placement service for landlords), and Mynd (property management platform for both Retail and Institutional investors). In 2025, Roofstock took an ownership stake in Casago (short-term rental management services), expanding our platform to support both long-term and short-term rental investment services.

Join us!

About the Role

Roofstock is building the next generation of AI-powered systems to transform the way single-family rentals are sourced, managed, and scaled. We’re looking for a Senior AI Engineer who thrives at the intersection of Generative AI, intelligent agents, and systems engineering.

You’ll help architect and deliver GenAI solutions that augment operations, automate decision-making, and enhance the experience for operators, investors, and residents. You’ll take an active role in shaping and delivering technical solutions, applying deep expertise in AI/ML, strong software engineering practices, and a collaborative mindset. You’ll play a key role in shaping our agentic infrastructure and partnering with teams across the organization to bring AI-powered capabilities to life.

Responsibilities

• Drive the design and implementation of scalable AI systems, with a focus on Generative AI, including LLMs, agentic workflows, and RAG pipelines, as well as applying machine learning where appropriate.
• Work cross-functionally with product, design, and operations teams to identify high-impact problems and develop AI-driven solutions.
• Lead initiatives to bring models from prototype to production, including evaluation, observability, and post-deployment monitoring.
• Contribute to the design of our agentic infrastructure, enabling tool use, task routing, and human-in-the-loop workflows.
• Collaborate with product, platform, and data teams to AI-enable internal services and tooling, design model interfaces, integrate data sources, and develop reusable orchestration patterns to support contextual, domain-specific intelligence.
• Own the reliability, performance, and operational health of services in production, including CI/CD workflows, infrastructure-as-code, and real-time monitoring.
• Mentor and support engineers, fostering a culture of technical excellence, collaboration, and continuous learning.
• Leverage your software engineering background to write clean, maintainable Python code, guide architectural decisions, and advocate for best practices in a fast-moving environment.
• Stay current on GenAI and ML trends, and evaluate emerging tools and techniques for practical integration.

Qualifications

• 5+ years of experience in AI engineering, with at least 2 years building or deploying Generative AI systems and intelligent agents in real-world environments. Experience with traditional ML concepts and pipelines is a plus.
• Experience building LLM-powered applications in real-world business contexts, such as AI copilots, agent workflows, or task automation systems.
• Hands-on experience with LLMs, agent frameworks (e.g. LangChain, LangGraph, or CrewAI), and RAG architectures.
• Deep proficiency in Python and strong fluency with Git, including CI workflows and collaborative development practices.
• Experience deploying and operating systems in AWS, including to