Forward Deployed AI Engineer

D.R. Horton•Arlington, TX

About The Position

D.R. Horton is seeking a Forward Deployed AI Engineer to turn emerging AI capabilities into practical solutions that address business problems. The role partners directly with business and technology teams to discover opportunities, rapidly prototype solutions, connect data and AI to real workflows, and move successful ideas into production. The engineer should be comfortable in both business discussions and coding, thrive in ambiguity, and demonstrate possibilities through working solutions. Success means delivering working solutions to business users within weeks, measurably improving workflows, and creating reusable patterns for other teams. The role involves embedding with business and field teams, developing AI-enabled applications and automations, and integrating enterprise data, models, APIs, and third-party capabilities. It works with Product, Architecture, Platform, Governance, and Security to define MVPs and support safe scaling, while leading field testing, adoption, feedback, and iteration. Overnight travel is required.

Requirements

Bachelor’s degree in Computer Science, Engineering, Data Science, Information Systems, or a related field, or equivalent experience.
5+ years of software engineering, AI engineering, solutions engineering, data engineering, or comparable experience.
Strong Python and/or TypeScript/JavaScript skills, with experience building APIs, applications, integrations, and AI-enabled solutions.
Practical experience with LLMs, RAG, agents, tool and MCP integration, prompt/context engineering, evaluation, document AI and unstructured data, and production AI patterns.
Exceptional communication and relationship-building skills, and willingness to spend significant time with business users and field teams.
Ability to work independently, take ownership, communicate clearly, and deliver results in an evolving environment.
Ability to build trusted relationships across the organization while balancing enterprise standards with business needs and operating realities.

Nice To Haves

Experience in forward-deployed engineering, consulting, solution architecture, product engineering, or startup environments.
Experience working across multiple model providers and AI platforms.
Experience in homebuilding, real estate, construction, mortgage, title, land development, sales, purchasing, finance, customer care, or another distributed operating business.
Experience working in a large enterprise with complex enterprise environments.
Experience founding, incubating, or building new products, capabilities, or businesses from the ground up.

Responsibilities

Embed with business and field teams to understand workflows, decisions, pain points, data, local variation, and measurable outcomes.
Rapidly prototype and productionize AI-enabled applications, agents, copilots, APIs, workflow automations, and decision-support experiences.
Connect enterprise data, models, APIs, and third-party capabilities into practical end-user solutions.
Work with Product to define MVP scope and with Architecture, Platform, Governance, and Security to ensure solutions can scale safely.
Drive field testing, feedback, adoption, and iteration, and translate lessons from one business unit into reusable enterprise patterns.
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 opportunities where data, AI, and digital capabilities can create business value, with an owner's mindset and a bias toward building, testing, and learning quickly.
Conduct all business in a professional and ethical manner.
Travel overnight.