Enterprise Architect - AI

Crown Equipment Corporation

1d•Hybrid

About The Position

Crown Equipment Corporation is a leading innovator in world-class forklift and material handling equipment and technology, committed to providing the customer with the safest, most efficient and ergonomic lift truck possible to lower their total cost of ownership. This role involves collaborating with organizational stakeholders to determine business goals related to AI and digital capabilities, and participating in the analysis and development of long-term strategic plans to align architectural objectives with enterprise business strategies. The Enterprise Architect will design, govern, and maintain AI architectures, platforms, integration patterns, and reference models consistent with enterprise standards. Key responsibilities include creating and maintaining architecture models, defining data storage, metadata management, model lifecycle management, and establishing data and AI governance. The position also requires documenting gaps between current and target state architectures, collaborating with software development, data, and AI teams, and participating in Architecture Working Groups. The architect will analyze the viability of enterprise and AI architecture, identify improvement opportunities, support build-versus-buy decisions for AI platforms, and foster relationships with business leaders and technology teams. Additionally, the role provides governance and oversight for the full AI solution lifecycle, implements responsible AI controls, and ensures compliance with security, privacy, regulatory, audit, and ethical standards, while publishing and maintaining architecture standards and guidelines.

Requirements

Bachelor’s degree in computer science, engineering, data science, or a related field
8+ years of related experience in enterprise architecture, AI/ML engineering, data engineering, or large-scale solution architecture
Experience designing and governing enterprise-scale AI and data-driven systems
Familiarity with architecture governance, security, privacy, and compliance frameworks

Nice To Haves

Deep hands-on experience with AI/ML engineering, MLOps/LLMops, and AI platform orchestration
Strong cloud, data, integration (API), and security architecture skills
Experience modeling architectures across business, information, application, data, AI, and technical layers
Experience evaluating emerging technologies and leading proofs of concept
Strong analytical, communication, leadership, and collaborative skills, with the ability to balance detailed analysis and big-picture thinking

Responsibilities

Collaborate with organizational stakeholders and internal colleagues to determine business goals and objectives related to AI and digital capabilities.
Recommend and participate in the analysis, evaluation, and development of long-term strategic plans to ensure architectural objectives are consistent with the enterprise’s long-term business strategies and goals.
Design, govern, and maintain AI architectures, platforms, integration patterns, and reference models that align with enterprise standards.
Create and maintain architecture models and documentation that reflect the Company’s business goals and strategies, including three-to-five-year target-state architectures.
Define data storage, metadata management, model lifecycle management, and usage rights for persistent data and AI assets, and establish appropriate data and AI governance.
Document gaps between current-state and target-state architectures and establish plans—including qualitative assessments of effort, cost, duration, and risk—to close those gaps.
Collaborate with software development, data, and AI teams to review solution objectives and constraints and determine conformance with enterprise and AI architecture standards.
Participate in and facilitate Architecture Working Groups supporting AI and enterprise architecture evolution.
Analyze the viability of the enterprise and AI architecture in the context of expected organizational and technological change.
Identify opportunities to improve AI-enabled systems to better support current and future business goals, improve scalability, and reduce cost or complexity.
Determine and support build-versus-buy decisions for AI platforms, tools, and services.
Establish and foster strong relationships with business leaders, technology teams, vendors, and service providers.
Provide governance and oversight for the full AI solution lifecycle, including data preparation, model development, validation, deployment, monitoring, and retirement, without assuming responsibility for delivery execution or operational ownership.
Implement and enforce responsible AI controls and ensure compliance with security, privacy, regulatory, audit, and ethical standards.
Publish and maintain architecture standards, guidelines, and documentation, ensuring the technical community understands and adheres to the approved enterprise and AI architecture direction.