Lead 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.

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.

D.R. Horton, Inc. is currently looking for a Lead Platform Engineer. The right candidate provides hands-on technical leadership for major domains of the enterprise Data & AI Foundation. This role leads engineering standards, complex implementations, operational excellence, and cross-team delivery across data services, DataOps, AI/ML platform capabilities, observability, automation, and hybrid infrastructure. The position coordinates technical work, mentors engineers, drives architecture within assigned domains, and ensures solutions are secure, reliable, scalable, supportable, and cost-effective.

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

• Lead engineering and operational ownership for major data platform domains, establishing technical standards for security, reliability, automation, workload management, observability, resilience, recovery, capacity, and cost governance
• Lead design and implementation of reusable platform services and automation using Python and/or other modern languages, APIs, infrastructure-as-code, CI/CD, Git-based workflows, testing, and configuration management
• Define and drive SRE/DataOps practices including SLIs, SLOs, service tiers, incident response, root-cause analysis, postmortems, automated remediation, availability, and recovery objectives
• Lead technical design for platform capabilities supporting analytics, machine learning, generative AI, semantic search, RAG, agents, model endpoints, vector services, model gateways, and intelligent applications
• Establish operational patterns for AI/ML services including deployment, inference, secrets, workload isolation, quotas, evaluation, monitoring, versioning, rollback, and lifecycle management
• Lead engineering integration across cloud and on-premises infrastructure, including containers/Kubernetes, storage, networking, GPU-enabled compute, resource scheduling, capacity, and observability
• Lead platform FinOps for assigned domains, including consumption analysis, forecasting inputs, utilization, unit economics, license optimization, vendor commitments, and cloud/on-prem workload placement recommendations
• Lead complex incidents, major changes, upgrades, migrations, proofs of concept, and operational-readiness assessments
• Review technical designs and code, mentor engineers, establish reusable patterns, and raise engineering quality across the team
• Partner with architecture, cybersecurity, infrastructure, data engineering, analytics, AI, sourcing, and business teams to resolve cross-platform decisions and dependencies
• Drive measurable improvements in availability, MTTR, automation coverage, self-service adoption, resource utilization, and unit cost
• Ability to travel overnight.
• Represent Data & AI Foundation engineering in architecture, security, governance, audit, sourcing, infrastructure, and strategic planning forums
• Lead technology evaluations and build/buy/partner analysis for assigned platform capabilities, considering interoperability, security, operational complexity, vendor lock-in, and total cost of ownership
• Provide technical leadership without direct supervisory responsibility, coordinate work across engineers and partners, and perform additional duties as assigned
• Conduct all business in a professional and ethical manner

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.

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.

D.R. Horton, Inc. is currently looking for a Lead Platform Engineer. The right candidate provides hands-on technical leadership for major domains of the enterprise Data & AI Foundation. This role leads engineering standards, complex implementations, operational excellence, and cross-team delivery across data services, DataOps, AI/ML platform capabilities, observability, automation, and hybrid infrastructure. The position coordinates technical work, mentors engineers, drives architecture within assigned domains, and ensures solutions are secure, reliable, scalable, supportable, and cost-effective.

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

• Lead engineering and operational ownership for major data platform domains, establishing technical standards for security, reliability, automation, workload management, observability, resilience, recovery, capacity, and cost governance
• Lead design and implementation of reusable platform services and automation using Python and/or other modern languages, APIs, infrastructure-as-code, CI/CD, Git-based workflows, testing, and configuration management
• Define and drive SRE/DataOps practices including SLIs, SLOs, service tiers, incident response, root-cause analysis, postmortems, automated remediation, availability, and recovery objectives
• Lead technical design for platform capabilities supporting analytics, machine learning, generative AI, semantic search, RAG, agents, model endpoints, vector services, model gateways, and intelligent applications
• Establish operational patterns for AI/ML services including deployment, inference, secrets, workload isolation, quotas, evaluation, monitoring, versioning, rollback, and lifecycle management
• Lead engineering integration across cloud and on-premises infrastructure, including containers/Kubernetes, storage, networking, GPU-enabled compute, resource scheduling, capacity, and observability
• Lead platform FinOps for assigned domains, including consumption analysis, forecasting inputs, utilization, unit economics, license optimization, vendor commitments, and cloud/on-prem workload placement recommendations
• Lead complex incidents, major changes, upgrades, migrations, proofs of concept, and operational-readiness assessments
• Review technical designs and code, mentor engineers, establish reusable patterns, and raise engineering quality across the team
• Partner with architecture, cybersecurity, infrastructure, data engineering, analytics, AI, sourcing, and business teams to resolve cross-platform decisions and dependencies
• Drive measurable improvements in availability, MTTR, automation coverage, self-service adoption, resource utilization, and unit cost
• Ability to travel overnight.
• Represent Data & AI Foundation engineering in architecture, security, governance, audit, sourcing, infrastructure, and strategic planning forums
• Lead technology evaluations and build/buy/partner analysis for assigned platform capabilities, considering interoperability, security, operational complexity, vendor lock-in, and total cost of ownership
• Provide technical leadership without direct supervisory responsibility, coordinate work across engineers and partners, and perform additional duties as assigned
• Conduct all business in a professional and ethical manner

Education and/or Experience

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent education and experience
• 7 or more years of progressive experience engineering and operating enterprise cloud or hybrid data platforms, DevOps platforms, AI/ML platforms, databases, integration platforms, or comparable services
• Expert-level experience in one or more platform domains with advanced breadth across security, performance, workload management, observability, resilience, automation, and cost governance
• Strong software and automation skills using Python and/or another modern language, APIs, infrastructure-as-code, CI/CD, Git, automated testing, and configuration management
• Demonstrated technical leadership establishing engineering standards, SRE/DataOps practices, recovery capabilities, operational controls, and platform roadmaps
• Experience leading complex platform implementations, migrations, incidents, architecture decisions, and cross-functional technical workstreams
• Advanced working knowledge of AI/ML platform patterns including LLM deployment, inference, RAG, vector search, model gateways, evaluation, observability, and lifecycle management.
• Ability to mentor engineers, influence technical decisions, and clearly communicate platform risk, architecture, value, cost, and trade-offs to senior stakeholders

Preferred Qualifications

• Advanced Snowflake, cloud, architecture, security, FinOps, SRE, Kubernetes, or responsible AI certification preferred
• Broad hands-on experience with Snowflake, Azure, Fivetran, dbt, Power BI/Microsoft Fabric, GitHub, Terraform/OpenTofu, Kubernetes, observability platforms, API management, and AI/ML platform services or comparable technologies preferred
• Experience with hybrid cloud/on-premises infrastructure, Linux, GPU-enabled compute, storage, networking, workload scheduling, hardware/software economics, metadata/catalog, governance, and open data formats such as Apache Iceberg preferred

Come join a winning team with a Fortune 500 company! We are growing fast and are looking for enthusiastic attitudes and team players to join our success. We offer an excellent benefits package including\:

• Medical, Dental and Vision
• 401(K)
• Employee Stock Purchase Plan
• Flex Spending Accounts
• Life & Disability Insurance
• Vacation, Sick, Personal Time and Company Holidays
• Multiple Voluntary and Company provided Benefits

Build YOUR future with D.R. Horton, America’s Builder.#WeBuildPeopleToo

Education and/or Experience

• Bachelor's degree in Computer Science, Information Systems, Engineering, or a related field, or equivalent education and experience
• 7 or more years of progressive experience engineering and operating enterprise cloud or hybrid data platforms, DevOps platforms, AI/ML platforms, databases, integration platforms, or comparable services
• Expert-level experience in one or more platform domains with advanced breadth across security, performance, workload management, observability, resilience, automation, and cost governance
• Strong software and automation skills using Python and/or another modern language, APIs, infrastructure-as-code, CI/CD, Git, automated testing, and configuration management
• Demonstrated technical leadership establishing engineering standards, SRE/DataOps practices, recovery capabilities, operational controls, and platform roadmaps
• Experience leading complex platform implementations, migrations, incidents, architecture decisions, and cross-functional technical workstreams
• Advanced working knowledge of AI/ML platform patterns including LLM deployment, inference, RAG, vector search, model gateways, evaluation, observability, and lifecycle management.
• Ability to mentor engineers, influence technical decisions, and clearly communicate platform risk, architecture, value, cost, and trade-offs to senior stakeholders

Preferred Qualifications

• Advanced Snowflake, cloud, architecture, security, FinOps, SRE, Kubernetes, or responsible AI certification preferred
• Broad hands-on experience with Snowflake, Azure, Fivetran, dbt, Power BI/Microsoft Fabric, GitHub, Terraform/OpenTofu, Kubernetes, observability platforms, API management, and AI/ML platform services or comparable technologies preferred
• Experience with hybrid cloud/on-premises infrastructure, Linux, GPU-enabled compute, storage, networking, workload scheduling, hardware/software economics, metadata/catalog, governance, and open data formats such as Apache Iceberg preferred

Come join a winning team with a Fortune 500 company! We are growing fast and are looking for enthusiastic attitudes and team players to join our success. We offer an excellent benefits package including\:

• Medical, Dental and Vision
• 401(K)
• Employee Stock Purchase Plan
• Flex Spending Accounts
• Life & Disability Insurance
• Vacation, Sick, Personal Time and Company Holidays
• Multiple Voluntary and Company provided Benefits

Build YOUR future with D.R. Horton, America’s Builder.#WeBuildPeopleToo