AI Platform Engineer

D.R. Horton, Inc., the largest homebuilder in the U.S., was founded in 1978 and is a publicly traded company on the New York Stock Exchange. It is engaged in the construction and sale of high-quality homes designed principally for the entry-level and first time move-up markets. The Company also provides mortgage financing and title services for homebuyers through its mortgage and title subsidiaries. Please visit our website at www.drhorton.com for more information.

D.R. Horton, Inc. is currently looking for an AI Platform Engineer. As the nation's largest homebuilder by volume, D.R. Horton is transforming how it uses data, AI, and digital solutions for the next generation of homebuilding, and we pair the reach of a national enterprise with a culture built on local ownership, practical innovation, and deep business partnerships. Our teams focus on solutions that work in the field and deliver real results, not technology for its own sake. In this role, you'll have a critical opportunity to shape modern capabilities that will influence how the company operates for years to come.

The AI Platform Engineer (also known as AI / ML Platform Engineer) will help build the modern platform capabilities that move machine learning and generative AI from experimentation into secure, reliable, and scalable production use. This role will engineer reusable services, automation, deployment patterns, observability, and infrastructure that make it easier for teams to develop and operate AI responsibly. The ideal candidate is a hands-on builder who enjoys solving complex platform problems and turning emerging technology into durable enterprise capability. This role's primary scope is the AI and ML platform layer\: model serving, gateways, agent runtimes, and the services that sit between models and applications. Success in this role means teams can take an AI use case from prototype to governed production in days rather than months, on a platform that is secure, observable, and cost-transparent.

Essential Duties and Responsibilities include the following. Other duties may be assigned.

• Engineer model and LLM deployment, inference, serving, gateway, evaluation, monitoring, registry, and lifecycle capabilities
• Build reusable platform services for RAG, embeddings, vector search, agents, secrets, API access, workload isolation, quotas, and observability
• Automate environments, deployments, testing, rollback, and infrastructure using CI/CD and infrastructure-as-code
• Support hybrid cloud and on-premises AI infrastructure including GPU-enabled compute, containers, storage, networking, scheduling, and capacity management
• Establish AI platform reliability, security, performance, utilization, and FinOps practices
• Represent the function in cross-functional discovery, architecture, governance, operational-readiness, and continuous-improvement activities as appropriate
• Stay current on relevant data, AI, digital, software, and industry practices and apply new capabilities when they create practical business value
• Identify, shape, and pilot new opportunities where data, AI, and digital capabilities can create business value, operating with an owner's mindset and a bias toward building, testing, and learning quickly
• Conduct all business in a professional and ethical manner to serve customers and increase the goodwill and profit of the company
• Ability to travel overnight