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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise AI Architect - **Company:** Dow - **Location:** Houston, TX, United States - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Artificial Intelligence, Data Analysis, Business Systems, Information Engineering, Data Governance, Data Infrastructure, Enterprise Architecture Framework, Machine Learning, SAP (Applications), Enterprise Data Management, Office365, IT Architecture, Generative AI, Agentic-AI, Togaf, Microsoft Copilot Studio, AI Platforms, Information Technology, Low-code, Machine Learning Operations, Virtual Agents, Databricks, Agent2Agent Protocol - **Published:** November 6, 2026 - **Apply:** https://dejobs.org/x/x/444AF710BA704C92B59AB59558E535BB/job/ ## About the Role * A minimum of a bachelor's degree or relevant military experience at or above a U.S. E5 ranking or Canadian Petty Officer 2nd Class or Sergeant or 16 years experience in lieu of a Bachelor's degree. Degree in information technology, Computer Science, Engineering, Data Science, or a related field preferred. * Experience developing enterprise architecture strategies, reference architectures, roadmaps, and governance processes in large, complex organizations. * Experience designing and implementing enterprise-scale AI, machine learning, analytics, automation, or digital transformation solutions. * Experience influencing technology strategy, architecture decisions, and investment priorities across multiple business functions and technology domains. * Experience working with business capabilities, end-to-end business processes, and enterprise transformation. * Experience in manufacturing, industrial, engineering, energy, or other complex operational environments is preferred. * A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency (green card) process. Preferred Qualifications * Architecture experience with Azure Databricks and modern enterprise data and AI platforms, including lakehouse, MLflow, model serving, agent frameworks, and unified data governance. * Experience architecting hybrid data & AI ecosystems (SAP, Databricks) . * Experience with Microsoft 365 Copilot and Copilot Studio for workforce productivity and low-code agent development. * Experience with enterprise data platforms and modern analytics technologies. * Knowledge of enterprise architecture frameworks such as TOGAF, and experience with enterprise architecture management tools. * Experience engaging technology suppliers, industry forums, advisory boards, or strategic technology partnerships. ## Description You are an experienced Enterprise Architect who wants to help a global materials science company turn artificial intelligence into real business value. In this role you will define Dow's enterprise AI architecture strategy: the reference architectures, standards, and roadmaps that enable business transformation and support Dow's corporate and business strategies. As the enterprise technical authority for AI architecture, you will develop integrated application, information, and technology architectures that make AI adoption scalable, secure, and responsible across manufacturing and operations, R&D, commercial, and corporate functions. You will partner with business leaders, architects, engineers, data professionals, and cybersecurity teams to guide strategic technology decisions and keep AI capabilities aligned with enterprise architecture principles and long-term business objectives. This is a senior individual contributor role in the Enterprise Architecture organization. You will influence enterprise strategy through technical leadership, architectural governance, and thought leadership. Responsibilities * Develop enterprise AI reference architectures, standards, roadmaps, and blueprints that align with business strategy and enable enterprise transformation. * Define and maintain integrated AI architecture capabilities across data, applications, processes, technology platforms, and governance so they support end-to-end business solutions. * Guide solution teams, architects, and technology partners with architectural direction, reusable patterns, and technical leadership for AI, generative AI, intelligent agents, and automation. * Set the standards for how AI agents are built, grounded on governed enterprise data, and connected to business systems and to one another through open interoperability patterns (for example, MCP and A2A). * Run architecture governance so strategic AI initiatives align with enterprise architecture principles, standards, and target-state architectures. * Evaluate emerging technologies, industry trends, and strategic supplier capabilities to find opportunities that advance AI adoption and strengthen enterprise capabilities. * Mentor architects and technology teams through architecture methods, reference architectures, position papers, and thought leadership that spread AI best practices across the enterprise., * Enterprise Architecture: Develops enterprise architecture strategies, capability models, and reference architectures that align technology capabilities with business needs. * Artificial Intelligence (AI) Architecture: Designs AI architectures across machine learning, generative AI, retrieval-augmented generation (RAG), intelligent agents, and modern AI/data platform ecosystems. * AI & Data Platform Architecture: Architects AI solutions on lakehouse platforms, including data engineering, the machine learning lifecycle, model serving, and unified data and AI governance. * Technology Strategy & Roadmapping: Develops strategic technology roadmaps, evaluates emerging technologies and industry trends, and translates future capabilities into actionable plans. * Architecture Governance: Establishes and applies architecture governance and risk-based decision-making practices to align technology investments with business objectives. * Executive Communication & Influence: Communicates complex technology and architecture concepts effectively to executives and stakeholders, using influential leadership and thought leadership to build alignment. * Financial Acumen & Business Value Assessment: Evaluates financial considerations, expected business value, and investment trade-offs to support technology prioritization and investment decisions.